From 29e8e8bbd43892c7fa146c165fdf128f786d6a7b Mon Sep 17 00:00:00 2001 From: Harpreet Date: Mon, 2 Nov 2015 16:20:08 +0530 Subject: README.rst added --- demos/README.rst | 5 + demos/qpipopt.dem.sce | 4 +- demos/qpipoptmat.dem.sce | 42 ++++ demos/qpipoptmat.dem.sce~ | 42 ++++ demos/sci_symphony.dem.gateway.sce | 2 +- demos/sci_symphony.dem.gateway.sce~ | 16 ++ demos/symphony.dem.sce | 113 ++++++++++ demos/symphonymat.dem.sce | 104 +++++++++ demos/symphonymat.dem.sce~ | 104 +++++++++ etc/README.rst | 14 ++ etc/README.rst~ | 0 etc/Symphony.quit | 24 ++ help/en_US/README.rst | 6 + help/en_US/README.rst~ | 5 + help/en_US/master_help.xml | 8 +- help/en_US/qpipopt.xml | 16 +- help/en_US/qpipoptmat.xml | 149 +++++++++++++ help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS | Bin 6478 -> 7157 bytes .../scilab_en_US_help/JavaHelpSearch/DOCS.TAB | 8 +- .../en_US/scilab_en_US_help/JavaHelpSearch/OFFSETS | Bin 255 -> 258 bytes .../scilab_en_US_help/JavaHelpSearch/POSITIONS | Bin 31519 -> 35046 bytes 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36 +++ macros/lib | Bin 480 -> 480 bytes macros/names | 2 +- macros/qpipopt.bin | Bin 29496 -> 33680 bytes macros/qpipopt.sci | 54 ++++- macros/qpipopt.sci~ | 233 ++++++++++++++++++++ macros/qpipoptmat.bin | Bin 31280 -> 38128 bytes macros/qpipoptmat.sci | 74 ++++++- macros/qpipoptmat.sci~ | 101 ++++++--- macros/setOptions.bin | Bin 3164 -> 3040 bytes macros/setOptions.sci | 17 +- macros/setOptions.sci~ | 40 ++++ macros/symphony.bin | Bin 43716 -> 43868 bytes macros/symphony.sci | 10 +- macros/symphony.sci~ | 227 +++++++++++++++++++ macros/symphony_call.bin | Bin 3932 -> 4064 bytes macros/symphony_call.sci | 4 +- macros/symphony_call.sci~ | 52 +++++ macros/symphonymat.bin | Bin 0 -> 45960 bytes macros/symphonymat.sci | 242 +++++++++++++++++++++ macros/symphonymat.sci~ | 242 +++++++++++++++++++++ sci_gateway/cpp/README.rst | 49 +++++ sci_gateway/cpp/README.rst~ | 0 sci_gateway/cpp/builder_gateway_cpp.sce | 6 +- sci_gateway/cpp/builder_gateway_cpp.sce~ | 149 +++++++++++++ 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thirdparty/linux/lib/x86/libcoinblas.so.1 create mode 100755 thirdparty/linux/lib/x86/libcoinblas.so.1.4.4 create mode 100755 thirdparty/linux/lib/x86/libcoinlapack.la create mode 120000 thirdparty/linux/lib/x86/libcoinlapack.so create mode 120000 thirdparty/linux/lib/x86/libcoinlapack.so.1 create mode 100755 thirdparty/linux/lib/x86/libcoinlapack.so.1.5.4 create mode 100755 thirdparty/linux/lib/x86/libcoinmumps.so.1.5.4 create mode 100755 thirdparty/linux/lib/x86/libipopt.so.1.10.4 diff --git a/demos/README.rst b/demos/README.rst new file mode 100644 index 0000000..5a4e36d --- /dev/null +++ b/demos/README.rst @@ -0,0 +1,5 @@ +DEMOS Files +=========== + +Demo files for the qpipopt and qpipoptmat which are used for Quadratic Programming. And also for symphony and symphonymat which are used for Mixed integer linear programming. + diff --git a/demos/qpipopt.dem.sce b/demos/qpipopt.dem.sce index 3b36ff1..d929a5c 100644 --- a/demos/qpipopt.dem.sce +++ b/demos/qpipopt.dem.sce @@ -17,7 +17,9 @@ ub=[10000; 100; 1.5; 100; 100; 1000]; p=[1; 2; 3; 4; 5; 6]; Q=eye(6,6); nbVar = 6; nbCon = 5; -[xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB) +x0 = repmat(0,nbVar,1); +param = list("MaxIter", 300, "CpuTime", 100); +[xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB,x0,param) halt() // Press return to continue //Find the value of x that minimize following function diff --git a/demos/qpipoptmat.dem.sce b/demos/qpipoptmat.dem.sce new file mode 100644 index 0000000..61263a8 --- /dev/null +++ b/demos/qpipoptmat.dem.sce @@ -0,0 +1,42 @@ +mode(1) +// +// Demo of qpipoptmat.sci +// + +//Find x in R^6 such that: +halt() // Press return to continue + +Aeq= [1,-1,1,0,3,1; +-1,0,-3,-4,5,6; +2,5,3,0,1,0]; +beq=[1; 2; 3]; +A= [0,1,0,1,2,-1; +-1,0,2,1,1,0]; +b = [-1; 2.5]; +lb=[-1000; -10000; 0; -1000; -1000; -1000]; +ub=[10000; 100; 1.5; 100; 100; 1000]; +x0 = repmat(0,6,1); +param = list("MaxIter", 300, "CpuTime", 100); +//and minimize 0.5*x'*Q*x + p'*x with +f=[1; 2; 3; 4; 5; 6]; H=eye(6,6); +[xopt,fopt,exitflag,output,lambda]=qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,[],param) +clear H f A b Aeq beq lb ub; +halt() // Press return to continue + +//Find the value of x that minimize following function +// f(x) = 0.5*x1^2 + x2^2 - x1*x2 - 2*x1 - 6*x2 +// Subject to: +// x1 + x2 ≤ 2 +// –x1 + 2x2 ≤ 2 +// 2x1 + x2 ≤ 3 +// 0 ≤ x1, 0 ≤ x2. +H = [1 -1; -1 2]; +f = [-2; -6]; +A = [1 1; -1 2; 2 1]; +b = [2; 2; 3]; +lb = [0; 0]; +ub = [%inf; %inf]; +[xopt,fopt,exitflag,output,lambda] = qpipoptmat(H,f,A,b,[],[],lb,ub) +halt() // Press return to continue + +//========= E N D === O F === D E M O =========// diff --git a/demos/qpipoptmat.dem.sce~ b/demos/qpipoptmat.dem.sce~ new file mode 100644 index 0000000..79628a7 --- /dev/null +++ b/demos/qpipoptmat.dem.sce~ @@ -0,0 +1,42 @@ +mode(1) +// +// Demo of qpipoptmat.sci +// + +//Find x in R^6 such that: +halt() // Press return to continue + +Aeq= [1,-1,1,0,3,1; +-1,0,-3,-4,5,6; +2,5,3,0,1,0]; +beq=[1; 2; 3]; +A= [0,1,0,1,2,-1; +-1,0,2,1,1,0]; +b = [-1; 2.5]; +lb=[-1000; -10000; 0; -1000; -1000; -1000]; +ub=[10000; 100; 1.5; 100; 100; 1000]; +x0 = repmat(0,6,1); +param = list("MaxIter", 300, "CpuTime", 100); +//and minimize 0.5*x'*Q*x + p'*x with +f=[1; 2; 3; 4; 5; 6]; H=eye(6,6); +[xopt,fopt,exitflag,output,lambda]=qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,[],param); +clear H f A b Aeq beq lb ub; +halt() // Press return to continue + +//Find the value of x that minimize following function +// f(x) = 0.5*x1^2 + x2^2 - x1*x2 - 2*x1 - 6*x2 +// Subject to: +// x1 + x2 ≤ 2 +// –x1 + 2x2 ≤ 2 +// 2x1 + x2 ≤ 3 +// 0 ≤ x1, 0 ≤ x2. +H = [1 -1; -1 2]; +f = [-2; -6]; +A = [1 1; -1 2; 2 1]; +b = [2; 2; 3]; +lb = [0; 0]; +ub = [%inf; %inf]; +[xopt,fopt,exitflag,output,lambda] = qpipoptmat(H,f,A,b,[],[],lb,ub) +halt() // Press return to continue + +//========= E N D === O F === D E M O =========// diff --git a/demos/sci_symphony.dem.gateway.sce b/demos/sci_symphony.dem.gateway.sce index 9256ca2..b3c52f4 100644 --- a/demos/sci_symphony.dem.gateway.sce +++ b/demos/sci_symphony.dem.gateway.sce @@ -11,6 +11,6 @@ demopath = get_absolute_file_path("sci_symphony.dem.gateway.sce"); -subdemolist = ["Symphony for knapsack", "symphony_knapsack.sce"]; +subdemolist = ["Symphony", "symphony.dem.sce"; "SymphonyMat", "symphonymat.dem.sce"; "Qpipopt", "qpipopt.dem.sce"; "QpipoptMat", "qpipoptmat.dem.sce";]; subdemolist(:,2) = demopath + subdemolist(:,2); diff --git a/demos/sci_symphony.dem.gateway.sce~ b/demos/sci_symphony.dem.gateway.sce~ new file mode 100644 index 0000000..9256ca2 --- /dev/null +++ b/demos/sci_symphony.dem.gateway.sce~ @@ -0,0 +1,16 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// Author: Harpreet Singh +// Organization: FOSSEE, IIT Bombay +// Email: harpreet.mertia@gmail.com +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt + +demopath = get_absolute_file_path("sci_symphony.dem.gateway.sce"); + +subdemolist = ["Symphony for knapsack", "symphony_knapsack.sce"]; + +subdemolist(:,2) = demopath + subdemolist(:,2); diff --git a/demos/symphony.dem.sce b/demos/symphony.dem.sce new file mode 100644 index 0000000..627c857 --- /dev/null +++ b/demos/symphony.dem.sce @@ -0,0 +1,113 @@ +mode(1) +// +// Demo of symphony.sci +// + +//A basic case : +// Objective function +c = [350*5,330*3,310*4,280*6,500,450,400,100] +// Lower Bound of variable +lb = repmat(0,1,8); +// Upper Bound of variables +ub = [repmat(1,1,4) repmat(%inf,1,4)]; +// Constraint Matrix +conMatrix = [5,3,4,6,1,1,1,1; +5*0.05,3*0.04,4*0.05,6*0.03,0.08,0.07,0.06,0.03; +5*0.03,3*0.03,4*0.04,6*0.04,0.06,0.07,0.08,0.09;] +// Lower Bound of constrains +conlb = [ 25; 1.25; 1.25] +// Upper Bound of constrains +conub = [ 25; 1.25; 1.25] +// Row Matrix for telling symphony that the is integer or not +isInt = [repmat(%t,1,4) repmat(%f,1,4)]; +xopt = [1 1 0 1 7.25 0 0.25 3.5] +fopt = [8495] +// Calling Symphony +[x,f,status,output] = symphony(8,3,c,isInt,lb,ub,conMatrix,conlb,conub,1) +halt() // Press return to continue + +// An advanced case where we set some options in symphony +// This problem is taken from +// P.C.Chu and J.E.Beasley +// "A genetic algorithm for the multidimensional knapsack problem", +// Journal of Heuristics, vol. 4, 1998, pp63-86. +// The problem to be solved is: +// Max sum{j=1,...,n} p(j)x(j) +// st sum{j=1,...,n} r(i,j)x(j) <= b(i) i=1,...,m +// x(j)=0 or 1 +// The function to be maximize i.e. P(j) +p = [ 504 803 667 1103 834 585 811 856 690 832 846 813 868 793 .. +825 1002 860 615 540 797 616 660 707 866 647 746 1006 608 .. +877 900 573 788 484 853 942 630 591 630 640 1169 932 1034 .. +957 798 669 625 467 1051 552 717 654 388 559 555 1104 783 .. +959 668 507 855 986 831 821 825 868 852 832 828 799 686 .. +510 671 575 740 510 675 996 636 826 1022 1140 654 909 799 .. +1162 653 814 625 599 476 767 954 906 904 649 873 565 853 1008 632] +//Constraint Matrix +conMatrix = [ +//Constraint 1 +42 41 523 215 819 551 69 193 582 375 367 478 162 898 .. +550 553 298 577 493 183 260 224 852 394 958 282 402 604 .. +164 308 218 61 273 772 191 117 276 877 415 873 902 465 .. +320 870 244 781 86 622 665 155 680 101 665 227 597 354 .. +597 79 162 998 849 136 112 751 735 884 71 449 266 420 .. +797 945 746 46 44 545 882 72 383 714 987 183 731 301 .. +718 91 109 567 708 507 983 808 766 615 554 282 995 946 651 298; +//Constraint 2 +509 883 229 569 706 639 114 727 491 481 681 948 687 941 .. +350 253 573 40 124 384 660 951 739 329 146 593 658 816 .. +638 717 779 289 430 851 937 289 159 260 930 248 656 833 .. +892 60 278 741 297 967 86 249 354 614 836 290 893 857 .. +158 869 206 504 799 758 431 580 780 788 583 641 32 653 .. +252 709 129 368 440 314 287 854 460 594 512 239 719 751 .. +708 670 269 832 137 356 960 651 398 893 407 477 552 805 881 850; +//Constraint 3 +806 361 199 781 596 669 957 358 259 888 319 751 275 177 .. +883 749 229 265 282 694 819 77 190 551 140 442 867 283 .. +137 359 445 58 440 192 485 744 844 969 50 833 57 877 .. +482 732 968 113 486 710 439 747 174 260 877 474 841 422 .. +280 684 330 910 791 322 404 403 519 148 948 414 894 147 .. +73 297 97 651 380 67 582 973 143 732 624 518 847 113 .. +382 97 905 398 859 4 142 110 11 213 398 173 106 331 254 447 ; +//Constraint 4 +404 197 817 1000 44 307 39 659 46 334 448 599 931 776 .. +263 980 807 378 278 841 700 210 542 636 388 129 203 110 .. +817 502 657 804 662 989 585 645 113 436 610 948 919 115 .. +967 13 445 449 740 592 327 167 368 335 179 909 825 614 .. +987 350 179 415 821 525 774 283 427 275 659 392 73 896 .. +68 982 697 421 246 672 649 731 191 514 983 886 95 846 .. +689 206 417 14 735 267 822 977 302 687 118 990 323 993 525 322; +//Constrain 5 +475 36 287 577 45 700 803 654 196 844 657 387 518 143 .. +515 335 942 701 332 803 265 922 908 139 995 845 487 100 .. +447 653 649 738 424 475 425 926 795 47 136 801 904 740 .. +768 460 76 660 500 915 897 25 716 557 72 696 653 933 .. +420 582 810 861 758 647 237 631 271 91 75 756 409 440 .. +483 336 765 637 981 980 202 35 594 689 602 76 767 693 .. +893 160 785 311 417 748 375 362 617 553 474 915 457 261 350 635 ; +]; +nbCon = size(conMatrix,1) +nbVar = size(conMatrix,2) +// Lower Bound of variables +lb = repmat(0,1,nbVar) +// Upper Bound of variables +ub = repmat(1,1,nbVar) +// Row Matrix for telling symphony that the is integer or not +isInt = repmat(%t,1,nbVar) +// Lower Bound of constrains +conLB=repmat(0,nbCon,1); +// Upper Bound of constraints +conUB=[11927 13727 11551 13056 13460 ]'; +options = list("time_limit", 25); +// The expected solution : +// Output variables +xopt = [0 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 0 1 .. +0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 1 0 .. +0 1 0 1 0 0 1 0 0 1 0 1 0 0 0 0 0 1 1 0 0 0 0 0 1 1 0 0 1 0 0 1 0] +// Optimal value +fopt = [ 24381 ] +// Calling Symphony +[x,f,status,output] = symphony(nbVar,nbCon,p,isInt,lb,ub,conMatrix,conLB,conUB,-1,options) +halt() // Press return to continue + +//========= E N D === O F === D E M O =========// diff --git a/demos/symphonymat.dem.sce b/demos/symphonymat.dem.sce new file mode 100644 index 0000000..441eb51 --- /dev/null +++ b/demos/symphonymat.dem.sce @@ -0,0 +1,104 @@ +mode(1) +// +// Demo of symphonymat.sci +// + +// Objective function +c = [350*5,330*3,310*4,280*6,500,450,400,100] +// Lower Bound of variable +lb = repmat(0,1,8); +// Upper Bound of variables +ub = [repmat(1,1,4) repmat(%inf,1,4)]; +// Constraint Matrix +Aeq = [5,3,4,6,1,1,1,1; +5*0.05,3*0.04,4*0.05,6*0.03,0.08,0.07,0.06,0.03; +5*0.03,3*0.03,4*0.04,6*0.04,0.06,0.07,0.08,0.09;] +beq = [ 25, 1.25, 1.25] +intcon = [1 2 3 4]; +// Calling Symphony +[x,f,status,output] = symphonymat(c,intcon,[],[],Aeq,beq,lb,ub) +halt() // Press return to continue + +// An advanced case where we set some options in symphony +// This problem is taken from +// P.C.Chu and J.E.Beasley +// "A genetic algorithm for the multidimensional knapsack problem", +// Journal of Heuristics, vol. 4, 1998, pp63-86. +// The problem to be solved is: +// Max sum{j=1,...,n} p(j)x(j) +// st sum{j=1,...,n} r(i,j)x(j) <= b(i) i=1,...,m +// x(j)=0 or 1 +// The function to be maximize i.e. P(j) +objCoef = -1*[ 504 803 667 1103 834 585 811 856 690 832 846 813 868 793 .. +825 1002 860 615 540 797 616 660 707 866 647 746 1006 608 .. +877 900 573 788 484 853 942 630 591 630 640 1169 932 1034 .. +957 798 669 625 467 1051 552 717 654 388 559 555 1104 783 .. +959 668 507 855 986 831 821 825 868 852 832 828 799 686 .. +510 671 575 740 510 675 996 636 826 1022 1140 654 909 799 .. +1162 653 814 625 599 476 767 954 906 904 649 873 565 853 1008 632] +//Constraint Matrix +conMatrix = [ //Constraint 1 +42 41 523 215 819 551 69 193 582 375 367 478 162 898 .. +550 553 298 577 493 183 260 224 852 394 958 282 402 604 .. +164 308 218 61 273 772 191 117 276 877 415 873 902 465 .. +320 870 244 781 86 622 665 155 680 101 665 227 597 354 .. +597 79 162 998 849 136 112 751 735 884 71 449 266 420 .. +797 945 746 46 44 545 882 72 383 714 987 183 731 301 .. +718 91 109 567 708 507 983 808 766 615 554 282 995 946 651 298; +//Constraint 2 +509 883 229 569 706 639 114 727 491 481 681 948 687 941 .. +350 253 573 40 124 384 660 951 739 329 146 593 658 816 .. +638 717 779 289 430 851 937 289 159 260 930 248 656 833 .. +892 60 278 741 297 967 86 249 354 614 836 290 893 857 .. +158 869 206 504 799 758 431 580 780 788 583 641 32 653 .. +252 709 129 368 440 314 287 854 460 594 512 239 719 751 .. +708 670 269 832 137 356 960 651 398 893 407 477 552 805 881 850; +//Constraint 3 +806 361 199 781 596 669 957 358 259 888 319 751 275 177 .. +883 749 229 265 282 694 819 77 190 551 140 442 867 283 .. +137 359 445 58 440 192 485 744 844 969 50 833 57 877 .. +482 732 968 113 486 710 439 747 174 260 877 474 841 422 .. +280 684 330 910 791 322 404 403 519 148 948 414 894 147 .. +73 297 97 651 380 67 582 973 143 732 624 518 847 113 .. +382 97 905 398 859 4 142 110 11 213 398 173 106 331 254 447 ; +//Constraint 4 +404 197 817 1000 44 307 39 659 46 334 448 599 931 776 .. +263 980 807 378 278 841 700 210 542 636 388 129 203 110 .. +817 502 657 804 662 989 585 645 113 436 610 948 919 115 .. +967 13 445 449 740 592 327 167 368 335 179 909 825 614 .. +987 350 179 415 821 525 774 283 427 275 659 392 73 896 .. +68 982 697 421 246 672 649 731 191 514 983 886 95 846 .. +689 206 417 14 735 267 822 977 302 687 118 990 323 993 525 322; +//Constrain 5 +475 36 287 577 45 700 803 654 196 844 657 387 518 143 .. +515 335 942 701 332 803 265 922 908 139 995 845 487 100 .. +447 653 649 738 424 475 425 926 795 47 136 801 904 740 .. +768 460 76 660 500 915 897 25 716 557 72 696 653 933 .. +420 582 810 861 758 647 237 631 271 91 75 756 409 440 .. +483 336 765 637 981 980 202 35 594 689 602 76 767 693 .. +893 160 785 311 417 748 375 362 617 553 474 915 457 261 350 635 ; +]; +nbVar = size(objCoef,2) +conUB=[11927 13727 11551 13056 13460 ]; +// Lower Bound of variables +lb = repmat(0,1,nbVar) +// Upper Bound of variables +ub = repmat(1,1,nbVar) +// Lower Bound of constrains +intcon = [] +for i = 1:nbVar +intcon = [intcon i]; +end +options = list("time_limit", 25); +// The expected solution : +// Output variables +xopt = [0 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 0 1 .. +0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 1 .. +0 0 1 0 0 1 0 1 0 0 1 0 0 1 0 1 0 0 0 0 0 1 1 0 0 0 0 0 1 1 0 0 1 0 0 1 0] +// Optimal value +fopt = [ 24381 ] +// Calling Symphony +[x,f,status,output] = symphonymat(objCoef,intcon,conMatrix,conUB,[],[],lb,ub,options); +halt() // Press return to continue + +//========= E N D === O F === D E M O =========// diff --git a/demos/symphonymat.dem.sce~ b/demos/symphonymat.dem.sce~ new file mode 100644 index 0000000..ef4d7cc --- /dev/null +++ b/demos/symphonymat.dem.sce~ @@ -0,0 +1,104 @@ +mode(1) +// +// Demo of symphonymat.sci +// + +// Objective function +c = [350*5,330*3,310*4,280*6,500,450,400,100] +// Lower Bound of variable +lb = repmat(0,1,8); +// Upper Bound of variables +ub = [repmat(1,1,4) repmat(%inf,1,4)]; +// Constraint Matrix +Aeq = [5,3,4,6,1,1,1,1; +5*0.05,3*0.04,4*0.05,6*0.03,0.08,0.07,0.06,0.03; +5*0.03,3*0.03,4*0.04,6*0.04,0.06,0.07,0.08,0.09;] +beq = [ 25, 1.25, 1.25] +intcon = [1 2 3 4]; +// Calling Symphony +[x,f,status,output] = symphonymat(c,intcon,[],[],Aeq,beq,lb,ub) +halt() // Press return to continue + +// An advanced case where we set some options in symphony +// This problem is taken from +// P.C.Chu and J.E.Beasley +// "A genetic algorithm for the multidimensional knapsack problem", +// Journal of Heuristics, vol. 4, 1998, pp63-86. +// The problem to be solved is: +// Max sum{j=1,...,n} p(j)x(j) +// st sum{j=1,...,n} r(i,j)x(j) <= b(i) i=1,...,m +// x(j)=0 or 1 +// The function to be maximize i.e. P(j) +objCoef = -1*[ 504 803 667 1103 834 585 811 856 690 832 846 813 868 793 .. +825 1002 860 615 540 797 616 660 707 866 647 746 1006 608 .. +877 900 573 788 484 853 942 630 591 630 640 1169 932 1034 .. +957 798 669 625 467 1051 552 717 654 388 559 555 1104 783 .. +959 668 507 855 986 831 821 825 868 852 832 828 799 686 .. +510 671 575 740 510 675 996 636 826 1022 1140 654 909 799 .. +1162 653 814 625 599 476 767 954 906 904 649 873 565 853 1008 632] +//Constraint Matrix +conMatrix = [ //Constraint 1 +42 41 523 215 819 551 69 193 582 375 367 478 162 898 .. +550 553 298 577 493 183 260 224 852 394 958 282 402 604 .. +164 308 218 61 273 772 191 117 276 877 415 873 902 465 .. +320 870 244 781 86 622 665 155 680 101 665 227 597 354 .. +597 79 162 998 849 136 112 751 735 884 71 449 266 420 .. +797 945 746 46 44 545 882 72 383 714 987 183 731 301 .. +718 91 109 567 708 507 983 808 766 615 554 282 995 946 651 298; +//Constraint 2 +509 883 229 569 706 639 114 727 491 481 681 948 687 941 .. +350 253 573 40 124 384 660 951 739 329 146 593 658 816 .. +638 717 779 289 430 851 937 289 159 260 930 248 656 833 .. +892 60 278 741 297 967 86 249 354 614 836 290 893 857 .. +158 869 206 504 799 758 431 580 780 788 583 641 32 653 .. +252 709 129 368 440 314 287 854 460 594 512 239 719 751 .. +708 670 269 832 137 356 960 651 398 893 407 477 552 805 881 850; +//Constraint 3 +806 361 199 781 596 669 957 358 259 888 319 751 275 177 .. +883 749 229 265 282 694 819 77 190 551 140 442 867 283 .. +137 359 445 58 440 192 485 744 844 969 50 833 57 877 .. +482 732 968 113 486 710 439 747 174 260 877 474 841 422 .. +280 684 330 910 791 322 404 403 519 148 948 414 894 147 .. +73 297 97 651 380 67 582 973 143 732 624 518 847 113 .. +382 97 905 398 859 4 142 110 11 213 398 173 106 331 254 447 ; +//Constraint 4 +404 197 817 1000 44 307 39 659 46 334 448 599 931 776 .. +263 980 807 378 278 841 700 210 542 636 388 129 203 110 .. +817 502 657 804 662 989 585 645 113 436 610 948 919 115 .. +967 13 445 449 740 592 327 167 368 335 179 909 825 614 .. +987 350 179 415 821 525 774 283 427 275 659 392 73 896 .. +68 982 697 421 246 672 649 731 191 514 983 886 95 846 .. +689 206 417 14 735 267 822 977 302 687 118 990 323 993 525 322; +//Constrain 5 +475 36 287 577 45 700 803 654 196 844 657 387 518 143 .. +515 335 942 701 332 803 265 922 908 139 995 845 487 100 .. +447 653 649 738 424 475 425 926 795 47 136 801 904 740 .. +768 460 76 660 500 915 897 25 716 557 72 696 653 933 .. +420 582 810 861 758 647 237 631 271 91 75 756 409 440 .. +483 336 765 637 981 980 202 35 594 689 602 76 767 693 .. +893 160 785 311 417 748 375 362 617 553 474 915 457 261 350 635 ; +]; +nbVar = size(objCoef,2) +conUB=[11927 13727 11551 13056 13460 ]; +// Lower Bound of variables +lb = repmat(0,1,nbVar) +// Upper Bound of variables +ub = repmat(1,1,nbVar) +// Lower Bound of constrains +intcon = [] +for i = 1:nbVar +intcon = [intcon i]; +end +options = list("time_limit", 25); +// The expected solution : +// Output variables +xopt = [0 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 0 1 .. +0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 1 .. +0 0 1 0 0 1 0 1 0 0 1 0 0 1 0 1 0 0 0 0 0 1 1 0 0 0 0 0 1 1 0 0 1 0 0 1 0] +// Optimal value +fopt = [ 24381 ] +// Calling Symphony +[x,f,status,output] = symphonymat(objCoef,intcon,conMatrix,conUB,[],[],lb,ub); +halt() // Press return to continue + +//========= E N D === O F === D E M O =========// diff --git a/etc/README.rst b/etc/README.rst new file mode 100644 index 0000000..2ffc09f --- /dev/null +++ b/etc/README.rst @@ -0,0 +1,14 @@ +DEMOS Files +=========== + +Start and exit files of the toolbox. + +.start +------- + +It will run a script when loader.sce is run from root toolbox directory. It will run loader files in all of the directories and link to important library. + +.quit +------- + +It will run a script when unloader.sce is run from root toolbox directory. It will unlink all of the important library. diff --git a/etc/README.rst~ b/etc/README.rst~ new file mode 100644 index 0000000..e69de29 diff --git a/etc/Symphony.quit b/etc/Symphony.quit index 13883fb..1eabef8 100644 --- a/etc/Symphony.quit +++ b/etc/Symphony.quit @@ -10,3 +10,27 @@ // http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt +function quitModule() + + etc_tlbx = get_absolute_file_path("Symphony.quit"); + etc_tlbx = getshortpathname(etc_tlbx); + root_tlbx = strncpy( etc_tlbx, length(etc_tlbx)-length("\etc\") ); + + //unlink libraries + [bOK, ilib] = c_link('FAMOS'); + if bOK then + ulink(ilib); + end + + // Remove Preferences GUI + // ============================================================================= + if getscilabmode() == "STD" then + removeModulePreferences(root_tlbx); + end + +endfunction + + +quitModule(); +clear quitModule; + diff --git a/help/en_US/README.rst b/help/en_US/README.rst new file mode 100644 index 0000000..95f8ace --- /dev/null +++ b/help/en_US/README.rst @@ -0,0 +1,6 @@ +Help XML +======== + +This directory contains all of help files in XML. These files are automatically generated by help_from_sci function by the help of comments in Macro. + +By the help of this we can generate html and jar files. diff --git a/help/en_US/README.rst~ b/help/en_US/README.rst~ new file mode 100644 index 0000000..8e9edd5 --- /dev/null +++ b/help/en_US/README.rst~ @@ -0,0 +1,5 @@ +Help XML +======== + +This directory contains all of help files in XML. These files are automatically generated by help_from_sci function by the help of comments in Macro. + diff --git a/help/en_US/master_help.xml b/help/en_US/master_help.xml index 791d3d0..67338f2 100644 --- a/help/en_US/master_help.xml +++ b/help/en_US/master_help.xml @@ -2,9 +2,9 @@ - + - + @@ -80,9 +80,9 @@ Symphony Toolbox &a6b85f6e0c98751f20b68663a23cb4cd2; -&a44928acec52adf395379e18fcff06730; +&a8549a3935858ed104f4749ca2243456a; &aca972f273143ecb39f56b42e4723ac67; -&a9953e61e8dd264a86df73772d3055e7f; +&a9910ada35b57b0581e8a77d145abac4a; Symphony Native Functions &acc223314e8a8bc290a13618df33a6237; diff --git a/help/en_US/qpipopt.xml b/help/en_US/qpipopt.xml index 144fe18..aecbe40 100644 --- a/help/en_US/qpipopt.xml +++ b/help/en_US/qpipopt.xml @@ -25,6 +25,8 @@ Calling Sequence xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB) + xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB,x0) + xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB,x0,param) [xopt,fopt,exitflag,output,lamda] = qpipopt( ... ) @@ -40,17 +42,21 @@ Q : a n x n symmetric matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem. p : - a 1 x n matrix of doubles, where n is number of variables, represents coefficients of linear in the quadratic problem + a n x 1 matrix of doubles, where n is number of variables, represents coefficients of linear in the quadratic problem LB : - a 1 x n matrix of doubles, where n is number of variables, contains lower bounds of the variables. + a n x 1 matrix of doubles, where n is number of variables, contains lower bounds of the variables. UB : - a 1 x n matrix of doubles, where n is number of variables, contains upper bounds of the variables. + a n x 1 matrix of doubles, where n is number of variables, contains upper bounds of the variables. conMatrix : a m x n matrix of doubles, where n is number of variables and m is number of constraints, contains matrix representing the constraint matrix conLB : a m x 1 matrix of doubles, where m is number of constraints, contains lower bounds of the constraints. conUB : a m x 1 matrix of doubles, where m is number of constraints, contains upper bounds of the constraints. + x0 : + a m x 1 matrix of doubles, where m is number of constraints, contains initial guess of variables. + param : + a list containing the the parameters to be set. xopt : a 1xn matrix of doubles, the computed solution of the optimization problem. fopt : @@ -104,7 +110,9 @@ ub=[10000; 100; 1.5; 100; 100; 1000]; p=[1; 2; 3; 4; 5; 6]; Q=eye(6,6); nbVar = 6; nbCon = 5; -[xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB) +x0 = repmat(0,nbVar,1); +param = list("MaxIter", 300, "CpuTime", 100); +[xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB,x0,param) ]]> diff --git a/help/en_US/qpipoptmat.xml b/help/en_US/qpipoptmat.xml new file mode 100644 index 0000000..eb8e737 --- /dev/null +++ b/help/en_US/qpipoptmat.xml @@ -0,0 +1,149 @@ + + + + + + + + qpipoptmat + Solves a linear quadratic problem. + + + + + Calling Sequence + + x = qpipoptmat(H,f) + x = qpipoptmat(H,f,A,b) + x = qpipoptmat(H,f,A,b,Aeq,beq) + x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub) + x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,x0) + x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,x0,param) + [xopt,fopt,exitflag,output,lamda] = qpipoptmat( ... ) + + + + + + Parameters + + H : + a n x n matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem. + f : + a n x 1 matrix of doubles, where n is number of variables, represents coefficients of linear in the quadratic problem + A : + a m x n matrix of doubles, represents the linear coefficients in the inequality constraints + b : + a column vector of doubles, represents the linear coefficients in the inequality constraints + Aeq : + a meq x n matrix of doubles, represents the linear coefficients in the equality constraints + beq : + a vector of doubles, represents the linear coefficients in the equality constraints + LB : + a n x 1 matrix of doubles, where n is number of variables, contains lower bounds of the variables. + UB : + a n x 1 matrix of doubles, where n is number of variables, contains upper bounds of the variables. + x0 : + a m x 1 matrix of doubles, where m is number of constraints, contains initial guess of variables. + param : + a list containing the the parameters to be set. + xopt : + a nx1 matrix of doubles, the computed solution of the optimization problem. + fopt : + a 1x1 matrix of doubles, the function value at x. + exitflag : + Integer identifying the reason the algorithm terminated. + output : + Structure containing information about the optimization. + lambda : + Structure containing the Lagrange multipliers at the solution x (separated by constraint type). + + + + + Description + +Search the minimum of a constrained linear quadratic optimization problem specified by : +find the minimum of f(x) such that + + + +\begin{eqnarray} +&\mbox{min}_{x} +& 1/2*x'*H*x + f'*x \\ +& \text{subject to} & A.x \leq b \\ +& & Aeq.x \leq beq \\ +& & lb \leq x \leq ub \\ +\end{eqnarray} + + + +We are calling IPOpt for solving the quadratic problem, IPOpt is a library written in C++. The code has been written by ​Andreas Wächter and ​Carl Laird. + + + + + + + Examples + + + + + Examples + + + + + Authors + + Keyur Joshi, Saikiran, Iswarya, Harpreet Singh + + + diff --git a/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS b/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS index 1b55b83..bf90ce2 100644 Binary files a/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS and b/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS differ diff --git a/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS.TAB b/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS.TAB index 3b7b18b..1b174ab 100644 --- a/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS.TAB +++ b/help/en_US/scilab_en_US_help/JavaHelpSearch/DOCS.TAB @@ -1,6 +1,2 @@ -e__y_u'\''uEIuSI0'@ [ -CP6N4*=h'  -rq\tX5 -C04 ҃bBG ҃_ -*]*紆X7 aH#J(0 Xtl4 -8PhU}h`TtW(h bEh2QUWe  d몙w_Ju“j_zf_!#qC &" ((!|dX(O 00ٽ(ȿ5F,質F,ήX, :0/40θ+,22:~̪2ҋ,. 0 ` \ No newline at end of file +e__y_u'\ _4_hT_e4s  _ +C`7FF$ 6(q\tX6±P$ tؠ`6 |*V@XR AX{0lHJ (3\/ P$2 YGGr $V(&QoZ(0Ou8?_)[j_z&eکY;7|T0 !,B(*2 Ur&(O 00мٱF6/tг]~m*`QӦBj/ //9Y.,d꪿e7erd̫t0 0˨, \ No newline at end of file diff --git a/help/en_US/scilab_en_US_help/JavaHelpSearch/OFFSETS b/help/en_US/scilab_en_US_help/JavaHelpSearch/OFFSETS index e290f81..ac2dfed 100644 Binary files a/help/en_US/scilab_en_US_help/JavaHelpSearch/OFFSETS and b/help/en_US/scilab_en_US_help/JavaHelpSearch/OFFSETS differ diff --git a/help/en_US/scilab_en_US_help/JavaHelpSearch/POSITIONS b/help/en_US/scilab_en_US_help/JavaHelpSearch/POSITIONS index 7fd9ab2..8be86f0 100644 Binary files a/help/en_US/scilab_en_US_help/JavaHelpSearch/POSITIONS and b/help/en_US/scilab_en_US_help/JavaHelpSearch/POSITIONS differ diff --git a/help/en_US/scilab_en_US_help/JavaHelpSearch/SCHEMA b/help/en_US/scilab_en_US_help/JavaHelpSearch/SCHEMA index 59337ab..c0f76d2 100644 --- a/help/en_US/scilab_en_US_help/JavaHelpSearch/SCHEMA +++ b/help/en_US/scilab_en_US_help/JavaHelpSearch/SCHEMA @@ -1,2 +1,2 @@ JavaSearch 1.0 -TMAP bs=2048 rt=1 fl=-1 id1=1347 id2=1 +TMAP bs=2048 rt=1 fl=-1 id1=1355 id2=1 diff --git a/help/en_US/scilab_en_US_help/JavaHelpSearch/TMAP b/help/en_US/scilab_en_US_help/JavaHelpSearch/TMAP index 0f25c4d..28f8966 100644 Binary files a/help/en_US/scilab_en_US_help/JavaHelpSearch/TMAP and b/help/en_US/scilab_en_US_help/JavaHelpSearch/TMAP differ diff --git a/help/en_US/scilab_en_US_help/_LaTeX_qpipoptmat.xml_1.png b/help/en_US/scilab_en_US_help/_LaTeX_qpipoptmat.xml_1.png new file mode 100644 index 0000000..b6e2743 Binary files /dev/null and b/help/en_US/scilab_en_US_help/_LaTeX_qpipoptmat.xml_1.png differ diff --git a/help/en_US/scilab_en_US_help/_LaTeX_symphonymat.xml_1.png b/help/en_US/scilab_en_US_help/_LaTeX_symphonymat.xml_1.png new file mode 100644 index 0000000..07dafd6 Binary files /dev/null and b/help/en_US/scilab_en_US_help/_LaTeX_symphonymat.xml_1.png differ diff --git a/help/en_US/scilab_en_US_help/index.html b/help/en_US/scilab_en_US_help/index.html index 2b1442a..12fb83c 100644 --- a/help/en_US/scilab_en_US_help/index.html +++ b/help/en_US/scilab_en_US_help/index.html @@ -38,7 +38,7 @@ -
  • qpipopt_mat — Solves a linear quadratic problem.
    • +
  • qpipoptmat — Solves a linear quadratic problem.
    • @@ -50,7 +50,7 @@ -
  • symphony_mat — Solves a mixed integer linear programming constrained optimization problem in intlinprog format.
    • +
  • symphonymat — Solves a mixed integer linear programming constrained optimization problem in intlinprog format.
  • Symphony Native Functions
    • sym_addConstr — Add a new constraint
      • diff --git a/help/en_US/scilab_en_US_help/jhelpmap.jhm b/help/en_US/scilab_en_US_help/jhelpmap.jhm index 1601f23..9dfdea5 100644 --- a/help/en_US/scilab_en_US_help/jhelpmap.jhm +++ b/help/en_US/scilab_en_US_help/jhelpmap.jhm @@ -4,9 +4,9 @@ - + - + diff --git a/help/en_US/scilab_en_US_help/jhelptoc.xml b/help/en_US/scilab_en_US_help/jhelptoc.xml index 463b86d..84c6d37 100644 --- a/help/en_US/scilab_en_US_help/jhelptoc.xml +++ b/help/en_US/scilab_en_US_help/jhelptoc.xml @@ -4,9 +4,9 @@ - + - + diff --git a/help/en_US/scilab_en_US_help/qpipopt.html b/help/en_US/scilab_en_US_help/qpipopt.html index fba4521..6659f44 100644 --- a/help/en_US/scilab_en_US_help/qpipopt.html +++ b/help/en_US/scilab_en_US_help/qpipopt.html @@ -20,7 +20,7 @@ - qpipopt_mat >> + qpipoptmat >> @@ -38,6 +38,8 @@

      Calling Sequence

      xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB)
+xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB,x0)
+xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB,x0,param)
 [xopt,fopt,exitflag,output,lamda] = qpipopt( ... )

      Parameters

      @@ -48,17 +50,21 @@
      Q :

      a n x n symmetric matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem.

      p : -

      a 1 x n matrix of doubles, where n is number of variables, represents coefficients of linear in the quadratic problem

      +

      a n x 1 matrix of doubles, where n is number of variables, represents coefficients of linear in the quadratic problem

      LB : -

      a 1 x n matrix of doubles, where n is number of variables, contains lower bounds of the variables.

      +

      a n x 1 matrix of doubles, where n is number of variables, contains lower bounds of the variables.

      UB : -

      a 1 x n matrix of doubles, where n is number of variables, contains upper bounds of the variables.

      +

      a n x 1 matrix of doubles, where n is number of variables, contains upper bounds of the variables.

      conMatrix :

      a m x n matrix of doubles, where n is number of variables and m is number of constraints, contains matrix representing the constraint matrix

      conLB :

      a m x 1 matrix of doubles, where m is number of constraints, contains lower bounds of the constraints.

      conUB :

      a m x 1 matrix of doubles, where m is number of constraints, contains upper bounds of the constraints.

      +
      x0 : +

      a m x 1 matrix of doubles, where m is number of constraints, contains initial guess of variables.

      +
      param : +

      a list containing the the parameters to be set.

      xopt :

      a 1xn matrix of doubles, the computed solution of the optimization problem.

      fopt : @@ -92,7 +98,9 @@ find the minimum of f(x) such that

      p=[1; 2; 3; 4; 5; 6]; Q=eye(6,6); nbVar = 6; nbCon = 5; -[xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB)
      +x0 = repmat(0,nbVar,1); +param = list("MaxIter", 300, "CpuTime", 100); +[xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB,x0,param)

      Examples

      //Find the value of x that minimize following function
@@ -130,7 +138,7 @@ find the minimum of f(x) such that
      		- qpipopt_mat >> + qpipoptmat >>
      diff --git a/help/en_US/scilab_en_US_help/qpipoptmat.html b/help/en_US/scilab_en_US_help/qpipoptmat.html new file mode 100644 index 0000000..5e7518e --- /dev/null +++ b/help/en_US/scilab_en_US_help/qpipoptmat.html @@ -0,0 +1,146 @@ + + + qpipoptmat + + + +
      + + + + +
      + << qpipopt + + + Symphony Toolbox + + + symphony >> + +
      +
      +
      + + + + Symphony Toolbox >> Symphony Toolbox > qpipoptmat + +

      +

      qpipoptmat

      +

      Solves a linear quadratic problem.

      + + +

      Calling Sequence

      + 
      x = qpipoptmat(H,f)
+x = qpipoptmat(H,f,A,b)
+x = qpipoptmat(H,f,A,b,Aeq,beq)
+x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub)
+x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,x0)
+x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,x0,param)
+[xopt,fopt,exitflag,output,lamda] = qpipoptmat( ... )
      + +

      Parameters

      +
      H : +

      a n x n matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem.

      +
      f : +

      a n x 1 matrix of doubles, where n is number of variables, represents coefficients of linear in the quadratic problem

      +
      A : +

      a m x n matrix of doubles, represents the linear coefficients in the inequality constraints

      +
      b : +

      a column vector of doubles, represents the linear coefficients in the inequality constraints

      +
      Aeq : +

      a meq x n matrix of doubles, represents the linear coefficients in the equality constraints

      +
      beq : +

      a vector of doubles, represents the linear coefficients in the equality constraints

      +
      LB : +

      a n x 1 matrix of doubles, where n is number of variables, contains lower bounds of the variables.

      +
      UB : +

      a n x 1 matrix of doubles, where n is number of variables, contains upper bounds of the variables.

      +
      x0 : +

      a m x 1 matrix of doubles, where m is number of constraints, contains initial guess of variables.

      +
      param : +

      a list containing the the parameters to be set.

      +
      xopt : +

      a nx1 matrix of doubles, the computed solution of the optimization problem.

      +
      fopt : +

      a 1x1 matrix of doubles, the function value at x.

      +
      exitflag : +

      Integer identifying the reason the algorithm terminated.

      +
      output : +

      Structure containing information about the optimization.

      +
      lambda : +

      Structure containing the Lagrange multipliers at the solution x (separated by constraint type).

      + +

      Description

      +

      Search the minimum of a constrained linear quadratic optimization problem specified by : +find the minimum of f(x) such that

      +

      +

      We are calling IPOpt for solving the quadratic problem, IPOpt is a library written in C++. The code has been written by ​Andreas Wächter and ​Carl Laird.

      +

      + +

      Examples

      + 
      //Find x in R^6 such that:
+
+Aeq= [1,-1,1,0,3,1;
+-1,0,-3,-4,5,6;
+2,5,3,0,1,0];
+beq=[1; 2; 3];
+A= [0,1,0,1,2,-1;
+-1,0,2,1,1,0];
+b = [-1; 2.5];
+lb=[-1000; -10000; 0; -1000; -1000; -1000];
+ub=[10000; 100; 1.5; 100; 100; 1000];
+x0 = repmat(0,6,1);
+param = list("MaxIter", 300, "CpuTime", 100);
+//and minimize 0.5*x'*Q*x + p'*x with
+f=[1; 2; 3; 4; 5; 6]; H=eye(6,6);
+[xopt,fopt,exitflag,output,lambda]=qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,[],param);
+clear H f A b Aeq beq lb ub;
      + +

      Examples

      + 
      //Find the value of x that minimize following function
+// f(x) = 0.5*x1^2 + x2^2 - x1*x2 - 2*x1 - 6*x2
+// Subject to:
+// x1 + x2 ≤ 2
+// –x1 + 2x2 ≤ 2
+// 2x1 + x2 ≤ 3
+// 0 ≤ x1, 0 ≤ x2.
+H = [1 -1; -1 2];
+f = [-2; -6];
+A = [1 1; -1 2; 2 1];
+b = [2; 2; 3];
+lb = [0; 0];
+ub = [%inf; %inf];
+[xopt,fopt,exitflag,output,lambda] = qpipoptmat(H,f,A,b,[],[],lb,ub)
      + +

      Authors

      +
      • Keyur Joshi, Saikiran, Iswarya, Harpreet Singh
      +
      + +
      + + + + + + +
      Report an issue
      + << qpipopt + + + Symphony Toolbox + + + symphony >> + +
      +
      +
      + + diff --git a/help/en_US/scilab_en_US_help/section_19f4f1e5726c01d683e8b82be0a7e910.html b/help/en_US/scilab_en_US_help/section_19f4f1e5726c01d683e8b82be0a7e910.html index ed07ab6..1e5e538 100644 --- a/help/en_US/scilab_en_US_help/section_19f4f1e5726c01d683e8b82be0a7e910.html +++ b/help/en_US/scilab_en_US_help/section_19f4f1e5726c01d683e8b82be0a7e910.html @@ -37,7 +37,7 @@ -
    • qpipopt_mat — Solves a linear quadratic problem.
      • +
    • qpipoptmat — Solves a linear quadratic problem.
      • @@ -49,7 +49,7 @@ -
    • symphony_mat — Solves a mixed integer linear programming constrained optimization problem in intlinprog format.
      • +
    • symphonymat — Solves a mixed integer linear programming constrained optimization problem in intlinprog format.
    • Symphony Native Functions
      • sym_addConstr — Add a new constraint
        • diff --git a/help/en_US/scilab_en_US_help/section_508f0b211d17ea6769714cc144e6b731.html b/help/en_US/scilab_en_US_help/section_508f0b211d17ea6769714cc144e6b731.html index 1d1b6d9..cf8c746 100644 --- a/help/en_US/scilab_en_US_help/section_508f0b211d17ea6769714cc144e6b731.html +++ b/help/en_US/scilab_en_US_help/section_508f0b211d17ea6769714cc144e6b731.html @@ -12,7 +12,7 @@
        - << symphony_mat + << symphonymat @@ -268,7 +268,7 @@
        Report an issue
        - << symphony_mat + << symphonymat diff --git a/help/en_US/scilab_en_US_help/symphony.html b/help/en_US/scilab_en_US_help/symphony.html index 0af9d1b..a1e3eea 100644 --- a/help/en_US/scilab_en_US_help/symphony.html +++ b/help/en_US/scilab_en_US_help/symphony.html @@ -12,7 +12,7 @@
        - << qpipopt_mat + << qpipoptmat @@ -20,7 +20,7 @@ - symphony_mat >> + symphonymat >>
        @@ -102,7 +102,7 @@ find the minimum or maximum of f(x) such that

        xopt = [1 1 0 1 7.25 0 0.25 3.5] fopt = [8495] // Calling Symphony -[x,f,iter] = symphony(8,3,c,isInt,lb,ub,conMatrix,conlb,conub,1);
      • +[x,f,status,output] = symphony(8,3,c,isInt,lb,ub,conMatrix,conlb,conub,1)

      Examples

      // An advanced case where we set some options in symphony
@@ -177,7 +177,7 @@ find the minimum or maximum of f(x) such that
      
 conLB=repmat(0,nbCon,1);
 // Upper Bound of constraints
 conUB=[11927 13727 11551 13056 13460 ]';
-options = ["time_limit" "25"]
+options = list("time_limit", 25);
 // The expected solution :
 // Output variables
 xopt = [0 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 0 1 ..
@@ -186,7 +186,7 @@ find the minimum or maximum of f(x) such that
      
 // Optimal value
 fopt = [ 24381 ]
 // Calling Symphony
-[x,f,iter]= symphony(nbVar,nbCon,p,isInt,lb,ub,conMatrix,conLB,conUB,-1,options)
      +[x,f,status,output] = symphony(nbVar,nbCon,p,isInt,lb,ub,conMatrix,conLB,conUB,-1,options)

      Authors

      • Keyur Joshi, Saikiran, Iswarya, Harpreet Singh
      @@ -197,7 +197,7 @@ find the minimum or maximum of f(x) such that

      Report an issue - << qpipopt_mat + << qpipoptmat @@ -205,7 +205,7 @@ find the minimum or maximum of f(x) such that

      - symphony_mat >> + symphonymat >> diff --git a/help/en_US/scilab_en_US_help/symphonymat.html b/help/en_US/scilab_en_US_help/symphonymat.html new file mode 100644 index 0000000..23ff2c6 --- /dev/null +++ b/help/en_US/scilab_en_US_help/symphonymat.html @@ -0,0 +1,201 @@ + + + symphonymat + + + +
      + + + + +
      + << symphony + + + Symphony Toolbox + + + Symphony Native Functions >> + +
      +
      +
      + + + + Symphony Toolbox >> Symphony Toolbox > symphonymat + +

      +

      symphonymat

      +

      Solves a mixed integer linear programming constrained optimization problem in intlinprog format.

      + + +

      Calling Sequence

      + 
      xopt = symphonymat(f,intcon,A,b)
+xopt = symphonymat(f,intcon,A,b,Aeq,beq)
+xopt = symphonymat(f,intcon,A,b,Aeq,beq,lb,ub)
+xopt = symphonymat(f,intcon,A,b,Aeq,beq,lb,ub,options)
+[xopt,fopt,status,output] = symphonymat( ... )
      + +

      Parameters

      +
      f : +

      a 1xn matrix of doubles, where n is number of variables, contains coefficients of the variables in the objective

      +
      intcon : +

      Vector of integer constraints, specified as a vector of positive integers. The values in intcon indicate the components of the decision variable x that are integer-valued. intcon has values from 1 through number of variable

      +
      A : +

      Linear inequality constraint matrix, specified as a matrix of doubles. A represents the linear coefficients in the constraints A*x ≤ b. A has size M-by-N, where M is the number of constraints and N is number of variables

      +
      b : +

      Linear inequality constraint vector, specified as a vector of doubles. b represents the constant vector in the constraints A*x ≤ b. b has length M, where A is M-by-N

      +
      Aeq : +

      Linear equality constraint matrix, specified as a matrix of doubles. Aeq represents the linear coefficients in the constraints Aeq*x = beq. Aeq has size Meq-by-N, where Meq is the number of constraints and N is number of variables

      +
      beq : +

      Linear equality constraint vector, specified as a vector of doubles. beq represents the constant vector in the constraints Aeq*x = beq. beq has length Meq, where Aeq is Meq-by-N.

      +
      lb : +

      Lower bounds, specified as a vector or array of doubles. lb represents the lower bounds elementwise in lb ≤ x ≤ ub.

      +
      ub : +

      Upper bounds, specified as a vector or array of doubles. ub represents the upper bounds elementwise in lb ≤ x ≤ ub.

      +
      options : +

      a list containing the the parameters to be set.

      +
      xopt : +

      a 1xn matrix of doubles, the computed solution of the optimization problem

      +
      fopt : +

      a 1x1 matrix of doubles, the function value at x

      +
      output : +

      The output data structure contains detailed informations about the optimization process.

      + +

      Description

      +

      Search the minimum or maximum of a constrained mixed integer linear programming optimization problem specified by : +find the minimum or maximum of f(x) such that

      +

      +

      We are calling SYMPHONY written in C by gateway files for the actual computation. SYMPHONY was originally written by ​Ted Ralphs, ​Menal Guzelsoy and ​Ashutosh Mahajan.

      +

      + +

      Examples

      + 
      // Objective function
+c = [350*5,330*3,310*4,280*6,500,450,400,100]
+// Lower Bound of variable
+lb = repmat(0,1,8);
+// Upper Bound of variables
+ub = [repmat(1,1,4) repmat(%inf,1,4)];
+// Constraint Matrix
+Aeq = [5,3,4,6,1,1,1,1;
+5*0.05,3*0.04,4*0.05,6*0.03,0.08,0.07,0.06,0.03;
+5*0.03,3*0.03,4*0.04,6*0.04,0.06,0.07,0.08,0.09;]
+beq = [ 25, 1.25, 1.25]
+intcon = [1 2 3 4];
+// Calling Symphony
+[x,f,status,output] = symphonymat(c,intcon,[],[],Aeq,beq,lb,ub)
      + +

      Examples

      + 
      // An advanced case where we set some options in symphony
+// This problem is taken from
+// P.C.Chu and J.E.Beasley
+// "A genetic algorithm for the multidimensional knapsack problem",
+// Journal of Heuristics, vol. 4, 1998, pp63-86.
+// The problem to be solved is:
+// Max  sum{j=1,...,n} p(j)x(j)
+// st   sum{j=1,...,n} r(i,j)x(j) <= b(i)       i=1,...,m
+//                     x(j)=0 or 1
+// The function to be maximize i.e. P(j)
+objCoef = -1*[   504 803 667 1103 834 585 811 856 690 832 846 813 868 793 ..
+825 1002 860 615 540 797 616 660 707 866 647 746 1006 608 ..
+877 900 573 788 484 853 942 630 591 630 640 1169 932 1034 ..
+957 798 669 625 467 1051 552 717 654 388 559 555 1104 783 ..
+959 668 507 855 986 831 821 825 868 852 832 828 799 686 ..
+510 671 575 740 510 675 996 636 826 1022 1140 654 909 799 ..
+1162 653 814 625 599 476 767 954 906 904 649 873 565 853 1008 632]
+//Constraint Matrix
+conMatrix = [   //Constraint 1
+42 41 523 215 819 551 69 193 582 375 367 478 162 898 ..
+550 553 298 577 493 183 260 224 852 394 958 282 402 604 ..
+164 308 218 61 273 772 191 117 276 877 415 873 902 465 ..
+320 870 244 781 86 622 665 155 680 101 665 227 597 354 ..
+597 79 162 998 849 136 112 751 735 884 71 449 266 420 ..
+797 945 746 46 44 545 882 72 383 714 987 183 731 301 ..
+718 91 109 567 708 507 983 808 766 615 554 282 995 946 651 298;
+//Constraint 2
+509 883 229 569 706 639 114 727 491 481 681 948 687 941 ..
+350 253 573 40 124 384 660 951 739 329 146 593 658 816 ..
+638 717 779 289 430 851 937 289 159 260 930 248 656 833 ..
+892 60 278 741 297 967 86 249 354 614 836 290 893 857 ..
+158 869 206 504 799 758 431 580 780 788 583 641 32 653 ..
+252 709 129 368 440 314 287 854 460 594 512 239 719 751 ..
+708 670 269 832 137 356 960 651 398 893 407 477 552 805 881 850;
+//Constraint 3
+806 361 199 781 596 669 957 358 259 888 319 751 275 177 ..
+883 749 229 265 282 694 819 77 190 551 140 442 867 283 ..
+137 359 445 58 440 192 485 744 844 969 50 833 57 877 ..
+482 732 968 113 486 710 439 747 174 260 877 474 841 422 ..
+280 684 330 910 791 322 404 403 519 148 948 414 894 147 ..
+73 297 97 651 380 67 582 973 143 732 624 518 847 113 ..
+382 97 905 398 859 4 142 110 11 213 398 173 106 331 254 447 ;
+//Constraint 4
+404 197 817 1000 44 307 39 659 46 334 448 599 931 776 ..
+263 980 807 378 278 841 700 210 542 636 388 129 203 110 ..
+817 502 657 804 662 989 585 645 113 436 610 948 919 115 ..
+967 13 445 449 740 592 327 167 368 335 179 909 825 614 ..
+987 350 179 415 821 525 774 283 427 275 659 392 73 896 ..
+68 982 697 421 246 672 649 731 191 514 983 886 95 846 ..
+689 206 417 14 735 267 822 977 302 687 118 990 323 993 525 322;
+//Constrain 5
+475 36 287 577 45 700 803 654 196 844 657 387 518 143 ..
+515 335 942 701 332 803 265 922 908 139 995 845 487 100 ..
+447 653 649 738 424 475 425 926 795 47 136 801 904 740 ..
+768 460 76 660 500 915 897 25 716 557 72 696 653 933 ..
+420 582 810 861 758 647 237 631 271 91 75 756 409 440 ..
+483 336 765 637 981 980 202 35 594 689 602 76 767 693 ..
+893 160 785 311 417 748 375 362 617 553 474 915 457 261 350 635 ;
+];
+nbVar = size(objCoef,2)
+conUB=[11927 13727 11551 13056 13460 ];
+// Lower Bound of variables
+lb = repmat(0,1,nbVar)
+// Upper Bound of variables
+ub = repmat(1,1,nbVar)
+// Lower Bound of constrains
+intcon = []
+for i = 1:nbVar
+intcon = [intcon i];
+end
+options = list("time_limit", 25);
+// The expected solution :
+// Output variables
+xopt = [0 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 0 1 ..
+0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 1 ..
+0 0 1 0 0 1 0 1 0 0 1 0 0 1 0 1 0 0 0 0 0 1 1 0 0 0 0 0 1 1 0 0 1 0 0 1 0]
+// Optimal value
+fopt = [ 24381 ]
+// Calling Symphony
+[x,f,status,output] = symphonymat(objCoef,intcon,conMatrix,conUB,[],[],lb,ub,options);
      + +

      Authors

      +
      • Keyur Joshi, Saikiran, Iswarya, Harpreet Singh
      +
      + +
      + + + + + + +
      Report an issue
      + << symphony + + + Symphony Toolbox + + + Symphony Native Functions >> + +
      +
      +
      + + diff --git a/help/en_US/symphony.xml b/help/en_US/symphony.xml index 86ad4b7..c33b95c 100644 --- a/help/en_US/symphony.xml +++ b/help/en_US/symphony.xml @@ -114,7 +114,8 @@ isInt = [repmat(%t,1,4) repmat(%f,1,4)]; xopt = [1 1 0 1 7.25 0 0.25 3.5] fopt = [8495] // Calling Symphony -[x,f,iter] = symphony(8,3,c,isInt,lb,ub,conMatrix,conlb,conub,1); +[x,f,status,output] = symphony(8,3,c,isInt,lb,ub,conMatrix,conlb,conub,1) + ]]> @@ -193,7 +194,7 @@ isInt = repmat(%t,1,nbVar) conLB=repmat(0,nbCon,1); // Upper Bound of constraints conUB=[11927 13727 11551 13056 13460 ]'; -options = ["time_limit" "25"] +options = list("time_limit", 25); // The expected solution : // Output variables xopt = [0 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 0 1 .. @@ -202,7 +203,7 @@ xopt = [0 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 0 1 .. // Optimal value fopt = [ 24381 ] // Calling Symphony -[x,f,iter]= symphony(nbVar,nbCon,p,isInt,lb,ub,conMatrix,conLB,conUB,-1,options) +[x,f,status,output] = symphony(nbVar,nbCon,p,isInt,lb,ub,conMatrix,conLB,conUB,-1,options) ]]> diff --git a/help/en_US/symphonymat.xml b/help/en_US/symphonymat.xml new file mode 100644 index 0000000..ca56363 --- /dev/null +++ b/help/en_US/symphonymat.xml @@ -0,0 +1,203 @@ + + + + + + + + symphonymat + Solves a mixed integer linear programming constrained optimization problem in intlinprog format. + + + + + Calling Sequence + + xopt = symphonymat(f,intcon,A,b) + xopt = symphonymat(f,intcon,A,b,Aeq,beq) + xopt = symphonymat(f,intcon,A,b,Aeq,beq,lb,ub) + xopt = symphonymat(f,intcon,A,b,Aeq,beq,lb,ub,options) + [xopt,fopt,status,output] = symphonymat( ... ) + + + + + + Parameters + + f : + a 1xn matrix of doubles, where n is number of variables, contains coefficients of the variables in the objective + intcon : + Vector of integer constraints, specified as a vector of positive integers. The values in intcon indicate the components of the decision variable x that are integer-valued. intcon has values from 1 through number of variable + A : + Linear inequality constraint matrix, specified as a matrix of doubles. A represents the linear coefficients in the constraints A*x ≤ b. A has size M-by-N, where M is the number of constraints and N is number of variables + b : + Linear inequality constraint vector, specified as a vector of doubles. b represents the constant vector in the constraints A*x ≤ b. b has length M, where A is M-by-N + Aeq : + Linear equality constraint matrix, specified as a matrix of doubles. Aeq represents the linear coefficients in the constraints Aeq*x = beq. Aeq has size Meq-by-N, where Meq is the number of constraints and N is number of variables + beq : + Linear equality constraint vector, specified as a vector of doubles. beq represents the constant vector in the constraints Aeq*x = beq. beq has length Meq, where Aeq is Meq-by-N. + lb : + Lower bounds, specified as a vector or array of doubles. lb represents the lower bounds elementwise in lb ≤ x ≤ ub. + ub : + Upper bounds, specified as a vector or array of doubles. ub represents the upper bounds elementwise in lb ≤ x ≤ ub. + options : + a list containing the the parameters to be set. + xopt : + a 1xn matrix of doubles, the computed solution of the optimization problem + fopt : + a 1x1 matrix of doubles, the function value at x + output : + The output data structure contains detailed informations about the optimization process. + + + + + Description + +Search the minimum or maximum of a constrained mixed integer linear programming optimization problem specified by : +find the minimum or maximum of f(x) such that + + + +\begin{eqnarray} +&\mbox{min}_{x} +& f(x) \\ +& \text{subject to} & conLB \leq C(x) \leq conUB \\ +& & lb \leq x \leq ub \\ +\end{eqnarray} + + + +We are calling SYMPHONY written in C by gateway files for the actual computation. SYMPHONY was originally written by ​Ted Ralphs, ​Menal Guzelsoy and ​Ashutosh Mahajan. + + + + + + + Examples + + + + + Examples + + + + + Authors + + Keyur Joshi, Saikiran, Iswarya, Harpreet Singh + + + diff --git a/jar/README.rst b/jar/README.rst new file mode 100644 index 0000000..ba5bc56 --- /dev/null +++ b/jar/README.rst @@ -0,0 +1,5 @@ +Help JAR +======== + +This is automatically generated file by the xml files. + diff --git a/jar/README.rst~ b/jar/README.rst~ new file mode 100644 index 0000000..e69de29 diff --git a/jar/scilab_en_US_help.jar b/jar/scilab_en_US_help.jar index 82b1a76..2f1f947 100644 Binary files a/jar/scilab_en_US_help.jar and b/jar/scilab_en_US_help.jar differ diff --git a/macros/README.rst b/macros/README.rst new file mode 100644 index 0000000..5a07f63 --- /dev/null +++ b/macros/README.rst @@ -0,0 +1,36 @@ +MACROS +====== + +These files mainly consist of functions for checking the input and calling the gateway functions + +symphony +-------- + +It takes the input in symphony style and checks the input. After all the checks call the symphony_call function. + +symphonymat +----------- + +It takes the input in symphony style and checks the input. After all the checks call the symphony_call function. + +symphony_call +------------- + +It calls the gateway functions to initialize, set options and to solve it. After that it will call the functions to get the solution for the problem. + +setOptions +---------- + +It will set the options in the symphony. + +qpipopt +------- + +It synatize the input and call solveqp in the ipopt style. + +qpipopt +------- + +It synatize the input and call solveqp in the quadprog style. + + diff --git a/macros/README.rst~ b/macros/README.rst~ new file mode 100644 index 0000000..5a07f63 --- /dev/null +++ b/macros/README.rst~ @@ -0,0 +1,36 @@ +MACROS +====== + +These files mainly consist of functions for checking the input and calling the gateway functions + +symphony +-------- + +It takes the input in symphony style and checks the input. After all the checks call the symphony_call function. + +symphonymat +----------- + +It takes the input in symphony style and checks the input. After all the checks call the symphony_call function. + +symphony_call +------------- + +It calls the gateway functions to initialize, set options and to solve it. After that it will call the functions to get the solution for the problem. + +setOptions +---------- + +It will set the options in the symphony. + +qpipopt +------- + +It synatize the input and call solveqp in the ipopt style. + +qpipopt +------- + +It synatize the input and call solveqp in the quadprog style. + + diff --git a/macros/lib b/macros/lib index 9b505b3..74bf87e 100644 Binary files a/macros/lib and b/macros/lib differ diff --git a/macros/names b/macros/names index 40e5934..e068c5a 100644 --- a/macros/names +++ b/macros/names @@ -3,4 +3,4 @@ qpipoptmat setOptions symphony symphony_call -symphony_mat +symphonymat diff --git a/macros/qpipopt.bin b/macros/qpipopt.bin index 0cdc0d9..07db2ad 100644 Binary files a/macros/qpipopt.bin and b/macros/qpipopt.bin differ diff --git a/macros/qpipopt.sci b/macros/qpipopt.sci index efcca01..8f3945e 100644 --- a/macros/qpipopt.sci +++ b/macros/qpipopt.sci @@ -16,16 +16,13 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin) // Calling Sequence // xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB) // xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB,x0) + // xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB,x0,param) // [xopt,fopt,exitflag,output,lamda] = qpipopt( ... ) // // Parameters // nbVar : a 1 x 1 matrix of doubles, number of variables // nbCon : a 1 x 1 matrix of doubles, number of constraints -<<<<<<< HEAD // Q : a n x n symmetric matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem. -======= - // Q : a n x n matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem. ->>>>>>> c2679735a3443017e003ca095d0476bae2dd8e40 // p : a n x 1 matrix of doubles, where n is number of variables, represents coefficients of linear in the quadratic problem // LB : a n x 1 matrix of doubles, where n is number of variables, contains lower bounds of the variables. // UB : a n x 1 matrix of doubles, where n is number of variables, contains upper bounds of the variables. @@ -33,6 +30,7 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin) // conLB : a m x 1 matrix of doubles, where m is number of constraints, contains lower bounds of the constraints. // conUB : a m x 1 matrix of doubles, where m is number of constraints, contains upper bounds of the constraints. // x0 : a m x 1 matrix of doubles, where m is number of constraints, contains initial guess of variables. + // param : a list containing the the parameters to be set. // xopt : a 1xn matrix of doubles, the computed solution of the optimization problem. // fopt : a 1x1 matrix of doubles, the function value at x. // exitflag : Integer identifying the reason the algorithm terminated. @@ -69,7 +67,9 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin) // p=[1; 2; 3; 4; 5; 6]; Q=eye(6,6); // nbVar = 6; // nbCon = 5; - // [xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB) + // x0 = repmat(0,nbVar,1); + // param = list("MaxIter", 300, "CpuTime", 100); + // [xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB,x0,param) // // Examples // //Find the value of x that minimize following function @@ -98,8 +98,8 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin) [lhs , rhs] = argn(); //To check the number of argument given by user - if ( rhs < 9 | rhs > 10 ) then - errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be 9 or 10"), "qpipopt", rhs); + if ( rhs < 9 | rhs > 11 ) then + errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be 9, 10 or 11"), "qpipopt", rhs); error(errmsg) end @@ -113,22 +113,53 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin) conMatrix = varargin(7); conLB = varargin(8); conUB = varargin(9); + - if ( rhs<10 ) then - x0 = repmat(0,1,nbVar) + if ( rhs<10 | size(varargin(10)) ==0 ) then + x0 = repmat(0,nbVar,1); else x0 = varargin(10); end + if ( rhs<11 ) then + param = list(); + else + param =varargin(11); + end + + if (modulo(size(param),2)) then + errmsg = msprintf(gettext("%s: Size of parameters should be even"), "qpipopt"); + error(errmsg); + end + + + options = list(.. + "MaxIter" , [3000], ... + "CpuTime" , [600] ... + ); + + for i = 1:(size(param))/2 + select param(2*i-1) + case "MaxIter" then + options(2*i) = param(2*i); + case "CpuTime" then + options(2*i) = param(2*i); + else + errmsg = msprintf(gettext("%s: Unrecognized parameter name ''%s''."), "qpipopt", param(2*i-1)); + error(errmsg) + end + end + //IPOpt wants it in row matrix form p = p'; LB = LB'; UB = UB'; conLB = conLB'; conUB = conUB'; + x0 = x0'; //Checking the Q matrix which needs to be a symmetric matrix - if ( Q~=Q') then + if ( ~isequal(Q,Q') ) then errmsg = msprintf(gettext("%s: Q is not a symmetric matrix"), "qpipopt"); error(errmsg); end @@ -182,7 +213,8 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin) error(errmsg); end - [xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,Q,p,conMatrix,conLB,conUB,LB,UB,x0); + + [xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,Q,p,conMatrix,conLB,conUB,LB,UB,x0,options); xopt = xopt'; exitflag = status; diff --git a/macros/qpipopt.sci~ b/macros/qpipopt.sci~ new file mode 100644 index 0000000..35e604b --- /dev/null +++ b/macros/qpipopt.sci~ @@ -0,0 +1,233 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// Author: Harpreet Singh +// Organization: FOSSEE, IIT Bombay +// Email: harpreet.mertia@gmail.com +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt + + +function [xopt,fopt,exitflag,output,lambda] = qpipopt (varargin) + // Solves a linear quadratic problem. + // + // Calling Sequence + // xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB) + // xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB,x0) + // xopt = qpipopt(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB,x0,param) + // [xopt,fopt,exitflag,output,lamda] = qpipopt( ... ) + // + // Parameters + // nbVar : a 1 x 1 matrix of doubles, number of variables + // nbCon : a 1 x 1 matrix of doubles, number of constraints + // Q : a n x n symmetric matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem. + // p : a n x 1 matrix of doubles, where n is number of variables, represents coefficients of linear in the quadratic problem + // LB : a n x 1 matrix of doubles, where n is number of variables, contains lower bounds of the variables. + // UB : a n x 1 matrix of doubles, where n is number of variables, contains upper bounds of the variables. + // conMatrix : a m x n matrix of doubles, where n is number of variables and m is number of constraints, contains matrix representing the constraint matrix + // conLB : a m x 1 matrix of doubles, where m is number of constraints, contains lower bounds of the constraints. + // conUB : a m x 1 matrix of doubles, where m is number of constraints, contains upper bounds of the constraints. + // x0 : a m x 1 matrix of doubles, where m is number of constraints, contains initial guess of variables. + // param : a list containing the the parameters to be set. + // xopt : a 1xn matrix of doubles, the computed solution of the optimization problem. + // fopt : a 1x1 matrix of doubles, the function value at x. + // exitflag : Integer identifying the reason the algorithm terminated. + // output : Structure containing information about the optimization. + // lambda : Structure containing the Lagrange multipliers at the solution x (separated by constraint type). + // + // Description + // Search the minimum of a constrained linear quadratic optimization problem specified by : + // find the minimum of f(x) such that + // + // + // \begin{eqnarray} + // &\mbox{min}_{x} + // & 1/2*x'*Q*x + p'*x \\ + // & \text{subject to} & conLB \leq C(x) \leq conUB \\ + // & & lb \leq x \leq ub \\ + // \end{eqnarray} + // + // + // We are calling IPOpt for solving the quadratic problem, IPOpt is a library written in C++. The code has been written by ​Andreas Wächter and ​Carl Laird. + // + // Examples + // //Find x in R^6 such that: + // conMatrix= [1,-1,1,0,3,1; + // -1,0,-3,-4,5,6; + // 2,5,3,0,1,0 + // 0,1,0,1,2,-1; + // -1,0,2,1,1,0]; + // conLB=[1;2;3;-%inf;-%inf]; + // conUB = [1;2;3;-1;2.5]; + // lb=[-1000;-10000; 0; -1000; -1000; -1000]; + // ub=[10000; 100; 1.5; 100; 100; 1000]; + // //and minimize 0.5*x'*Q*x + p'*x with + // p=[1; 2; 3; 4; 5; 6]; Q=eye(6,6); + // nbVar = 6; + // nbCon = 5; + // x0 = repmat(0,nbVar,1); + // param = list("MaxIter", 300, "CpuTime", 100); + // [xopt,fopt,exitflag,output,lambda]=qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB,x0,param) + // + // Examples + // //Find the value of x that minimize following function + // // f(x) = 0.5*x1^2 + x2^2 - x1*x2 - 2*x1 - 6*x2 + // // Subject to: + // // x1 + x2 ≤ 2 + // // –x1 + 2x2 ≤ 2 + // // 2x1 + x2 ≤ 3 + // // 0 ≤ x1, 0 ≤ x2. + // Q = [1 -1; -1 2]; + // p = [-2; -6]; + // conMatrix = [1 1; -1 2; 2 1]; + // conUB = [2; 2; 3]; + // conLB = [-%inf; -%inf; -%inf]; + // lb = [0; 0]; + // ub = [%inf; %inf]; + // nbVar = 2; + // nbCon = 3; + // [xopt,fopt,exitflag,output,lambda] = qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB) + // + // Authors + // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh + + +//To check the number of input and output argument + [lhs , rhs] = argn(); + +//To check the number of argument given by user + if ( rhs < 9 | rhs > 11 ) then + errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be 9, 10 or 11"), "qpipopt", rhs); + error(errmsg) + end + + + nbVar = varargin(1); + nbCon = varargin(2); + Q = varargin(3); + p = varargin(4); + LB = varargin(5); + UB = varargin(6); + conMatrix = varargin(7); + conLB = varargin(8); + conUB = varargin(9); + + + if ( rhs<10 | size(varargin(10)) ==0 ) then + x0 = repmat(0,nbVar,1); + else + x0 = varargin(10); + end + + if ( rhs<11 ) then + param = []; + else + param =varargin(11); + end + + if (modulo(size(param),2)) then + errmsg = msprintf(gettext("%s: Size of parameters should be even"), "qpipopt"); + error(errmsg); + end + + + options = list(.. + "MaxIter" , [3000], ... + "CpuTime" , [600] ... + ); + + for i = 1:(size(param))/2 + + select param(2*i-1) + case "MaxIter" then + options(1) = param(2*i); + case "CpuTime" then + options(3) = param(2*i); + else + errmsg = msprintf(gettext("%s: Unrecognized parameter name ''%s''."), "qpipopt", param(2*i-1)); + error(errmsg) + end + end + + //IPOpt wants it in row matrix form + p = p'; + LB = LB'; + UB = UB'; + conLB = conLB'; + conUB = conUB'; + x0 = x0'; + + //Checking the Q matrix which needs to be a symmetric matrix + if ( ~isequal(Q,Q') ) then + errmsg = msprintf(gettext("%s: Q is not a symmetric matrix"), "qpipopt"); + error(errmsg); + end + + //Check the size of Q which should equal to the number of variable + if ( size(Q) ~= [nbVar nbVar]) then + errmsg = msprintf(gettext("%s: The Size of Q is not equal to the number of variables"), "qpipopt"); + error(errmsg); + end + + //Check the size of p which should equal to the number of variable + if ( size(p,2) ~= [nbVar]) then + errmsg = msprintf(gettext("%s: The Size of p is not equal to the number of variables"), "qpipopt"); + error(errmsg); + end + + + //Check the size of constraint which should equal to the number of variables + if ( size(conMatrix,2) ~= nbVar) then + errmsg = msprintf(gettext("%s: The size of constraints is not equal to the number of variables"), "qpipopt"); + error(errmsg); + end + + //Check the size of Lower Bound which should equal to the number of variables + if ( size(LB,2) ~= nbVar) then + errmsg = msprintf(gettext("%s: The Lower Bound is not equal to the number of variables"), "qpipopt"); + error(errmsg); + end + + //Check the size of Upper Bound which should equal to the number of variables + if ( size(UB,2) ~= nbVar) then + errmsg = msprintf(gettext("%s: The Upper Bound is not equal to the number of variables"), "qpipopt"); + error(errmsg); + end + + //Check the size of constraints of Lower Bound which should equal to the number of constraints + if ( size(conLB,2) ~= nbCon) then + errmsg = msprintf(gettext("%s: The Lower Bound of constraints is not equal to the number of constraints"), "qpipopt"); + error(errmsg); + end + + //Check the size of constraints of Upper Bound which should equal to the number of constraints + if ( size(conUB,2) ~= nbCon) then + errmsg = msprintf(gettext("%s: The Upper Bound of constraints is not equal to the number of constraints"), "qpipopt"); + error(errmsg); + end + + //Check the size of initial of variables which should equal to the number of variables + if ( size(x0,2) ~= nbVar) then + errmsg = msprintf(gettext("%s: The initial guess of variables is not equal to the number of variables"), "qpipopt"); + error(errmsg); + end + + + [xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,Q,p,conMatrix,conLB,conUB,LB,UB,x0,options); + + xopt = xopt'; + exitflag = status; + output = struct("Iterations" , []); + output.Iterations = iter; + lambda = struct("lower" , [], .. + "upper" , [], .. + "constraint" , []); + + lambda.lower = Zl; + lambda.upper = Zu; + lambda.constraint = lmbda; + + +endfunction diff --git a/macros/qpipoptmat.bin b/macros/qpipoptmat.bin index 68c3988..668402c 100644 Binary files a/macros/qpipoptmat.bin and b/macros/qpipoptmat.bin differ diff --git a/macros/qpipoptmat.sci b/macros/qpipoptmat.sci index 2f3e911..6ae20c0 100644 --- a/macros/qpipoptmat.sci +++ b/macros/qpipoptmat.sci @@ -14,11 +14,12 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin) // Solves a linear quadratic problem. // // Calling Sequence - // xopt = qpipoptmat(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB) // x = qpipoptmat(H,f) // x = qpipoptmat(H,f,A,b) // x = qpipoptmat(H,f,A,b,Aeq,beq) // x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub) + // x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,x0) + // x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,x0,param) // [xopt,fopt,exitflag,output,lamda] = qpipoptmat( ... ) // // Parameters @@ -30,6 +31,8 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin) // beq : a vector of doubles, represents the linear coefficients in the equality constraints // LB : a n x 1 matrix of doubles, where n is number of variables, contains lower bounds of the variables. // UB : a n x 1 matrix of doubles, where n is number of variables, contains upper bounds of the variables. + // x0 : a m x 1 matrix of doubles, where m is number of constraints, contains initial guess of variables. + // param : a list containing the the parameters to be set. // xopt : a nx1 matrix of doubles, the computed solution of the optimization problem. // fopt : a 1x1 matrix of doubles, the function value at x. // exitflag : Integer identifying the reason the algorithm terminated. @@ -64,9 +67,11 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin) // b = [-1; 2.5]; // lb=[-1000; -10000; 0; -1000; -1000; -1000]; // ub=[10000; 100; 1.5; 100; 100; 1000]; + // x0 = repmat(0,6,1); + // param = list("MaxIter", 300, "CpuTime", 100); // //and minimize 0.5*x'*Q*x + p'*x with // f=[1; 2; 3; 4; 5; 6]; H=eye(6,6); - // [xopt,fopt,exitflag,output,lambda]=qpipoptmat(H,f,A,b,Aeq,beq,lb,ub) + // [xopt,fopt,exitflag,output,lambda]=qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,[],param) // clear H f A b Aeq beq lb ub; // // Examples @@ -93,8 +98,8 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin) [lhs , rhs] = argn(); //To check the number of argument given by user - if ( rhs < 2 | rhs == 3 | rhs == 5 | rhs == 7 | rhs > 8 ) then - errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be in the set of [2 4 6 8]"), "qpipopt", rhs); + if ( rhs < 2 | rhs == 3 | rhs == 5 | rhs == 7 | rhs > 10 ) then + errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be in the set of [2 4 6 8 9 10]"), "qpipoptmat", rhs); error(errmsg) end @@ -126,7 +131,50 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin) LB = varargin(7); UB = varargin(8); end - + + + if ( rhs<9 | size(varargin(9)) ==0 ) then + x0 = repmat(0,nbVar,1) + else + x0 = varargin(9); + end + + if ( rhs<10 ) then + param = list(); + else + param =varargin(10); + end + + + if (modulo(size(param),2)) then + errmsg = msprintf(gettext("%s: Size of parameters should be even"), "qpipoptmat"); + error(errmsg); + end + + if (modulo(size(param),2)) then + errmsg = msprintf(gettext("%s: Size of parameters should be even"), "qpipoptmat"); + error(errmsg); + end + + + options = list(.. + "MaxIter" , [3000], ... + "CpuTime" , [600] ... + ); + + for i = 1:(size(param))/2 + + select param(2*i-1) + case "MaxIter" then + options(2*i-1) = param(2*i); + case "CpuTime" then + options(2*i-1) = param(2*i); + else + errmsg = msprintf(gettext("%s: Unrecognized parameter name ''%s''."), "qpipoptmat", param(2*i-1)); + error(errmsg) + end + end + nbConInEq = size(A,1); nbConEq = size(Aeq,1); @@ -168,33 +216,41 @@ function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin) error(errmsg); end -//Check the size of Upper Bound which should equal to the number of variables + //Check the size of Upper Bound which should equal to the number of variables if ( size(UB,1) ~= nbVar) then errmsg = msprintf(gettext("%s: The Upper Bound is not equal to the number of variables"), "qpipoptmat"); error(errmsg); end -//Check the size of constraints of Lower Bound which should equal to the number of constraints + //Check the size of constraints of Lower Bound which should equal to the number of constraints if ( size(b,1) ~= nbConInEq & size(b,1) ~= 0) then errmsg = msprintf(gettext("%s: The Lower Bound of inequality constraints is not equal to the number of constraints"), "qpipoptmat"); error(errmsg); end -//Check the size of constraints of Upper Bound which should equal to the number of constraints + //Check the size of constraints of Upper Bound which should equal to the number of constraints if ( size(beq,1) ~= nbConEq & size(beq,1) ~= 0) then errmsg = msprintf(gettext("%s: The Upper Bound of equality constraints is not equal to the number of constraints"), "qpipoptmat"); error(errmsg); end + + //Check the size of initial of variables which should equal to the number of variables + if ( size(x0,1) ~= nbVar) then + errmsg = msprintf(gettext("%s: The initial guess of variables is not equal to the number of variables"), "qpipoptmat"); + error(errmsg); + end + //Converting it into ipopt format f = f'; LB = LB'; UB = UB'; + x0 = x0'; conMatrix = [Aeq;A]; nbCon = size(conMatrix,1); conLB = [beq; repmat(-%inf,nbConInEq,1)]'; conUB = [beq;b]' ; - [xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,H,f,conMatrix,conLB,conUB,LB,UB); + [xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,H,f,conMatrix,conLB,conUB,LB,UB,x0,options); xopt = xopt'; exitflag = status; diff --git a/macros/qpipoptmat.sci~ b/macros/qpipoptmat.sci~ index 4c72216..e29da8f 100644 --- a/macros/qpipoptmat.sci~ +++ b/macros/qpipoptmat.sci~ @@ -10,16 +10,17 @@ // http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt -function [xopt,fopt,exitflag,output,lambda] = qpipopt_mat (varargin) +function [xopt,fopt,exitflag,output,lambda] = qpipoptmat (varargin) // Solves a linear quadratic problem. // // Calling Sequence - // xopt = qpipopt_mat(nbVar,nbCon,Q,p,LB,UB,conMatrix,conLB,conUB) - // x = qpipopt_mat(H,f) - // x = qpipopt_mat(H,f,A,b) - // x = qpipopt_mat(H,f,A,b,Aeq,beq) - // x = qpipopt_mat(H,f,A,b,Aeq,beq,lb,ub) - // [xopt,fopt,exitflag,output,lamda] = qpipopt_mat( ... ) + // x = qpipoptmat(H,f) + // x = qpipoptmat(H,f,A,b) + // x = qpipoptmat(H,f,A,b,Aeq,beq) + // x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub) + // x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,x0) + // x = qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,x0,param) + // [xopt,fopt,exitflag,output,lamda] = qpipoptmat( ... ) // // Parameters // H : a n x n matrix of doubles, where n is number of variables, represents coefficients of quadratic in the quadratic problem. @@ -30,6 +31,8 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt_mat (varargin) // beq : a vector of doubles, represents the linear coefficients in the equality constraints // LB : a n x 1 matrix of doubles, where n is number of variables, contains lower bounds of the variables. // UB : a n x 1 matrix of doubles, where n is number of variables, contains upper bounds of the variables. + // x0 : a m x 1 matrix of doubles, where m is number of constraints, contains initial guess of variables. + // param : a list containing the the parameters to be set. // xopt : a nx1 matrix of doubles, the computed solution of the optimization problem. // fopt : a 1x1 matrix of doubles, the function value at x. // exitflag : Integer identifying the reason the algorithm terminated. @@ -64,9 +67,11 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt_mat (varargin) // b = [-1; 2.5]; // lb=[-1000; -10000; 0; -1000; -1000; -1000]; // ub=[10000; 100; 1.5; 100; 100; 1000]; + // x0 = repmat(0,6,1); + // param = list("MaxIter", 300, "CpuTime", 100); // //and minimize 0.5*x'*Q*x + p'*x with // f=[1; 2; 3; 4; 5; 6]; H=eye(6,6); - // [xopt,fopt,exitflag,output,lambda]=qpipopt_mat(H,f,A,b,Aeq,beq,lb,ub) + // [xopt,fopt,exitflag,output,lambda]=qpipoptmat(H,f,A,b,Aeq,beq,lb,ub,[],param) // clear H f A b Aeq beq lb ub; // // Examples @@ -83,7 +88,7 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt_mat (varargin) // b = [2; 2; 3]; // lb = [0; 0]; // ub = [%inf; %inf]; - // [xopt,fopt,exitflag,output,lambda] = qpipopt_mat(H,f,A,b,[],[],lb,ub) + // [xopt,fopt,exitflag,output,lambda] = qpipoptmat(H,f,A,b,[],[],lb,ub) // // Authors // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh @@ -93,8 +98,8 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt_mat (varargin) [lhs , rhs] = argn(); //To check the number of argument given by user - if ( rhs < 2 | rhs == 3 | rhs == 5 | rhs == 7 | rhs > 8 ) then - errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be in the set of [2 4 6 8]"), "qpipopt", rhs); + if ( rhs < 2 | rhs == 3 | rhs == 5 | rhs == 7 | rhs > 10 ) then + errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be in the set of [2 4 6 8 9 10]"), "qpipoptmat", rhs); error(errmsg) end @@ -126,75 +131,121 @@ function [xopt,fopt,exitflag,output,lambda] = qpipopt_mat (varargin) LB = varargin(7); UB = varargin(8); end - + + + if ( rhs<10 | size(varargin(9)) ==0 ) then + x0 = repmat(0,nbVar,1) + else + x0 = varargin(9); + end + + if ( rhs<11 ) then + param = list(); + else + param =varargin(10); + end + + + if (modulo(size(param),2)) then + errmsg = msprintf(gettext("%s: Size of parameters should be even"), "qpipoptmat"); + error(errmsg); + end + + + options = list(.. + "MaxIter" , [3000], ... + "CpuTime" , [600] ... + ); + + for i = 1:(size(param))/2 + + select param(2*i-1) + case "MaxIter" then + options(2*i-1) = param(2*i); + case "CpuTime" then + options(2*i-1) = param(2*i); + else + errmsg = msprintf(gettext("%s: Unrecognized parameter name ''%s''."), "qpipoptmat", param(2*i-1)); + error(errmsg) + end + end + nbConInEq = size(A,1); nbConEq = size(Aeq,1); //Checking the H matrix which needs to be a symmetric matrix if ( H~=H') then - errmsg = msprintf(gettext("%s: H is not a symmetric matrix"), "qpipopt_mat"); + errmsg = msprintf(gettext("%s: H is not a symmetric matrix"), "qpipoptmat"); error(errmsg); end //Check the size of H which should equal to the number of variable if ( size(H) ~= [nbVar nbVar]) then - errmsg = msprintf(gettext("%s: The Size of H is not equal to the number of variables"), "qpipopt"); + errmsg = msprintf(gettext("%s: The Size of H is not equal to the number of variables"), "qpipoptmat"); error(errmsg); end //Check the size of f which should equal to the number of variable if ( size(f,1) ~= [nbVar]) then - errmsg = msprintf(gettext("%s: The Size of f is not equal to the number of variables"), "qpipopt"); + errmsg = msprintf(gettext("%s: The Size of f is not equal to the number of variables"), "qpipoptmat"); error(errmsg); end //Check the size of inequality constraint which should be equal to the number of variables if ( size(A,2) ~= nbVar & size(A,2) ~= 0) then - errmsg = msprintf(gettext("%s: The size of inequality constraints is not equal to the number of variables"), "qpipopt"); + errmsg = msprintf(gettext("%s: The size of inequality constraints is not equal to the number of variables"), "qpipoptmat"); error(errmsg); end //Check the size of equality constraint which should be equal to the number of variables if ( size(Aeq,2) ~= nbVar & size(Aeq,2) ~= 0 ) then - errmsg = msprintf(gettext("%s: The size of equality constraints is not equal to the number of variables"), "qpipopt"); + errmsg = msprintf(gettext("%s: The size of equality constraints is not equal to the number of variables"), "qpipoptmat"); error(errmsg); end //Check the size of Lower Bound which should be equal to the number of variables if ( size(LB,1) ~= nbVar) then - errmsg = msprintf(gettext("%s: The Lower Bound is not equal to the number of variables"), "qpipopt"); + errmsg = msprintf(gettext("%s: The Lower Bound is not equal to the number of variables"), "qpipoptmat"); error(errmsg); end -//Check the size of Upper Bound which should equal to the number of variables + //Check the size of Upper Bound which should equal to the number of variables if ( size(UB,1) ~= nbVar) then - errmsg = msprintf(gettext("%s: The Upper Bound is not equal to the number of variables"), "qpipopt"); + errmsg = msprintf(gettext("%s: The Upper Bound is not equal to the number of variables"), "qpipoptmat"); error(errmsg); end -//Check the size of constraints of Lower Bound which should equal to the number of constraints + //Check the size of constraints of Lower Bound which should equal to the number of constraints if ( size(b,1) ~= nbConInEq & size(b,1) ~= 0) then - errmsg = msprintf(gettext("%s: The Lower Bound of inequality constraints is not equal to the number of constraints"), "qpipopt"); + errmsg = msprintf(gettext("%s: The Lower Bound of inequality constraints is not equal to the number of constraints"), "qpipoptmat"); error(errmsg); end -//Check the size of constraints of Upper Bound which should equal to the number of constraints + //Check the size of constraints of Upper Bound which should equal to the number of constraints if ( size(beq,1) ~= nbConEq & size(beq,1) ~= 0) then - errmsg = msprintf(gettext("%s: The Upper Bound of equality constraints is not equal to the number of constraints"), "qp_ipopt"); + errmsg = msprintf(gettext("%s: The Upper Bound of equality constraints is not equal to the number of constraints"), "qpipoptmat"); error(errmsg); end + + //Check the size of initial of variables which should equal to the number of variables + if ( size(x0,1) ~= nbVar) then + errmsg = msprintf(gettext("%s: The initial guess of variables is not equal to the number of variables"), "qpipoptmat"); + error(errmsg); + end + //Converting it into ipopt format f = f'; LB = LB'; UB = UB'; + x0 = x0'; conMatrix = [Aeq;A]; nbCon = size(conMatrix,1); conLB = [beq; repmat(-%inf,nbConInEq,1)]'; conUB = [beq;b]' ; - [xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,H,f,conMatrix,conLB,conUB,LB,UB); + [xopt,fopt,status,iter,Zl,Zu,lmbda] = solveqp(nbVar,nbCon,H,f,conMatrix,conLB,conUB,LB,UB,x0,options); xopt = xopt'; exitflag = status; diff --git a/macros/setOptions.bin b/macros/setOptions.bin index c5a69df..8d23e73 100644 Binary files a/macros/setOptions.bin and b/macros/setOptions.bin differ diff --git a/macros/setOptions.sci b/macros/setOptions.sci index 138e577..68aad02 100644 --- a/macros/setOptions.sci +++ b/macros/setOptions.sci @@ -12,9 +12,8 @@ function setOptions(varargin) options = varargin(1); - nbOpt = size(options,2); + nbOpt = size(options); - value = strtod(options) if (nbOpt~=0) then for i = 1:(nbOpt/2) @@ -22,21 +21,19 @@ function setOptions(varargin) //Setting the parameters //Check if the given parameter is String - if (value(2*i) == %nan ) then - sym_setStrParam(options(2*i - 1),value(2*i)); + if (type(options(2*i)) == 10 ) then + sym_setStrParam(options(2*i - 1),options(2*i)); //Check if the given parameter is Double - elseif(type(value(2*i))==1) then - sym_setDblParam(options(2*i - 1),value(2*i)); + elseif(type(options(2*i))==1) then + sym_setDblParam(options(2*i - 1),options(2*i)); //Check if the given parameter is Integer - elseif(type(value(2*i))==8) + elseif(type(options(2*i))==8) sym_setIntParam(options(2*i - 1),options(2*i)); end - - end + end end - endfunction diff --git a/macros/setOptions.sci~ b/macros/setOptions.sci~ new file mode 100644 index 0000000..ef5c36c --- /dev/null +++ b/macros/setOptions.sci~ @@ -0,0 +1,40 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// Author: Harpreet Singh +// Organization: FOSSEE, IIT Bombay +// Email: harpreet.mertia@gmail.com +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt + +function setOptions(varargin) + + options = varargin(1); + nbOpt = size(options); + + + if (nbOpt~=0) then + for i = 1:(nbOpt/2) + + //Setting the parameters + + //Check if the given parameter is String + if (type(options(2*i)) == 10 ) then + sym_setStrParam(options(2*i - 1),options(2*i)); + + //Check if the given parameter is Double + elseif(type(options(2*i))==1) then + sym_setDblParam(options(2*i - 1),options(2*i)); + + //Check if the given parameter is Integer + elseif(type(options(2*i))==8) + sym_setIntParam(options(2*i - 1),options(2*i)); + end + + end + end + +endfunction + diff --git a/macros/symphony.bin b/macros/symphony.bin index ae6c958..d2aa822 100644 Binary files a/macros/symphony.bin and b/macros/symphony.bin differ diff --git a/macros/symphony.sci b/macros/symphony.sci index f221160..9677720 100644 --- a/macros/symphony.sci +++ b/macros/symphony.sci @@ -71,7 +71,8 @@ function [xopt,fopt,status,output] = symphony (varargin) // xopt = [1 1 0 1 7.25 0 0.25 3.5] // fopt = [8495] // // Calling Symphony - // [x,f,iter] = symphony(8,3,c,isInt,lb,ub,conMatrix,conlb,conub,1); + // [x,f,status,output] = symphony(8,3,c,isInt,lb,ub,conMatrix,conlb,conub,1) + // // Examples // // An advanced case where we set some options in symphony // // This problem is taken from @@ -145,7 +146,7 @@ function [xopt,fopt,status,output] = symphony (varargin) // conLB=repmat(0,nbCon,1); // // Upper Bound of constraints // conUB=[11927 13727 11551 13056 13460 ]'; - // options = ["time_limit" "25"] + // options = list("time_limit", 25); // // The expected solution : // // Output variables // xopt = [0 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 0 1 .. @@ -154,7 +155,7 @@ function [xopt,fopt,status,output] = symphony (varargin) // // Optimal value // fopt = [ 24381 ] // // Calling Symphony - // [x,f,iter]= symphony(nbVar,nbCon,p,isInt,lb,ub,conMatrix,conLB,conUB,-1,options) + // [x,f,status,output] = symphony(nbVar,nbCon,p,isInt,lb,ub,conMatrix,conLB,conUB,-1,options) // // Authors // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh @@ -185,7 +186,7 @@ function [xopt,fopt,status,output] = symphony (varargin) end if (rhs<11) then - options = []; + options = list(); else options = varargin(11); end @@ -224,4 +225,3 @@ function [xopt,fopt,status,output] = symphony (varargin) [xopt,fopt,status,output] = symphony_call(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB,objSense,options); endfunction - diff --git a/macros/symphony.sci~ b/macros/symphony.sci~ new file mode 100644 index 0000000..d5c8e44 --- /dev/null +++ b/macros/symphony.sci~ @@ -0,0 +1,227 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// Author: Harpreet Singh +// Organization: FOSSEE, IIT Bombay +// Email: harpreet.mertia@gmail.com +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt + +function [xopt,fopt,status,output] = symphony (varargin) + // Solves a mixed integer linear programming constrained optimization problem. + // + // Calling Sequence + // xopt = symphony(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB) + // xopt = symphony(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB,objSense) + // xopt = symphony(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB,objSense,options) + // [xopt,fopt,status,output] = symphony( ... ) + // + // Parameters + // nbVar : a 1 x 1 matrix of doubles, number of variables + // nbCon : a 1 x 1 matrix of doubles, number of constraints + // objCoeff : a 1 x n matrix of doubles, where n is number of variables, contains coefficients of the variables in the objective + // isInt : a 1 x n matrix of boolean, where n is number of variables, representing wether a variable is constrained to be an integer + // LB : a 1 x n matrix of doubles, where n is number of variables, contains lower bounds of the variables. Bound can be negative infinity + // UB : a 1 x n matrix of doubles, where n is number of variables, contains upper bounds of the variables. Bound can be infinity + // conMatrix : a m x n matrix of doubles, where n is number of variables and m is number of constraints, contains matrix representing the constraint matrix + // conLB : a m x 1 matrix of doubles, where m is number of constraints, contains lower bounds of the constraints. + // conUB : a m x 1 matrix of doubles, where m is number of constraints, contains upper bounds of the constraints + // objSense : The sense (maximization/minimization) of the objective. Use 1(sym_minimize ) or -1 (sym_maximize) here + // options : a 1xq marix of string, provided to set the paramters in symphony + // xopt : a 1xn matrix of doubles, the computed solution of the optimization problem + // fopt : a 1x1 matrix of doubles, the function value at x + // status : status flag from symphony + // output : The output data structure contains detailed informations about the optimization process. + // + // Description + // Search the minimum or maximum of a constrained mixed integer linear programming optimization problem specified by : + // find the minimum or maximum of f(x) such that + // + // + // \begin{eqnarray} + // &\mbox{min}_{x} + // & f(x) \\ + // & \text{subject to} & conLB \leq C(x) \leq conUB \\ + // & & lb \leq x \leq ub \\ + // \end{eqnarray} + // + // + // We are calling SYMPHONY written in C by gateway files for the actual computation. SYMPHONY was originally written by ​Ted Ralphs, ​Menal Guzelsoy and ​Ashutosh Mahajan. + // + // Examples + // //A basic case : + // // Objective function + // c = [350*5,330*3,310*4,280*6,500,450,400,100] + // // Lower Bound of variable + // lb = repmat(0,1,8); + // // Upper Bound of variables + // ub = [repmat(1,1,4) repmat(%inf,1,4)]; + // // Constraint Matrix + // conMatrix = [5,3,4,6,1,1,1,1; + // 5*0.05,3*0.04,4*0.05,6*0.03,0.08,0.07,0.06,0.03; + // 5*0.03,3*0.03,4*0.04,6*0.04,0.06,0.07,0.08,0.09;] + // // Lower Bound of constrains + // conlb = [ 25; 1.25; 1.25] + // // Upper Bound of constrains + // conub = [ 25; 1.25; 1.25] + // // Row Matrix for telling symphony that the is integer or not + // isInt = [repmat(%t,1,4) repmat(%f,1,4)]; + // xopt = [1 1 0 1 7.25 0 0.25 3.5] + // fopt = [8495] + // // Calling Symphony + // [x,f,status,output] = symphony(8,3,c,isInt,lb,ub,conMatrix,conlb,conub,1) + // + // Examples + // // An advanced case where we set some options in symphony + // // This problem is taken from + // // P.C.Chu and J.E.Beasley + // // "A genetic algorithm for the multidimensional knapsack problem", + // // Journal of Heuristics, vol. 4, 1998, pp63-86. + // // The problem to be solved is: + // // Max sum{j=1,...,n} p(j)x(j) + // // st sum{j=1,...,n} r(i,j)x(j) <= b(i) i=1,...,m + // // x(j)=0 or 1 + // // The function to be maximize i.e. P(j) + // p = [ 504 803 667 1103 834 585 811 856 690 832 846 813 868 793 .. + // 825 1002 860 615 540 797 616 660 707 866 647 746 1006 608 .. + // 877 900 573 788 484 853 942 630 591 630 640 1169 932 1034 .. + // 957 798 669 625 467 1051 552 717 654 388 559 555 1104 783 .. + // 959 668 507 855 986 831 821 825 868 852 832 828 799 686 .. + // 510 671 575 740 510 675 996 636 826 1022 1140 654 909 799 .. + // 1162 653 814 625 599 476 767 954 906 904 649 873 565 853 1008 632] + // //Constraint Matrix + // conMatrix = [ + // //Constraint 1 + // 42 41 523 215 819 551 69 193 582 375 367 478 162 898 .. + // 550 553 298 577 493 183 260 224 852 394 958 282 402 604 .. + // 164 308 218 61 273 772 191 117 276 877 415 873 902 465 .. + // 320 870 244 781 86 622 665 155 680 101 665 227 597 354 .. + // 597 79 162 998 849 136 112 751 735 884 71 449 266 420 .. + // 797 945 746 46 44 545 882 72 383 714 987 183 731 301 .. + // 718 91 109 567 708 507 983 808 766 615 554 282 995 946 651 298; + // //Constraint 2 + // 509 883 229 569 706 639 114 727 491 481 681 948 687 941 .. + // 350 253 573 40 124 384 660 951 739 329 146 593 658 816 .. + // 638 717 779 289 430 851 937 289 159 260 930 248 656 833 .. + // 892 60 278 741 297 967 86 249 354 614 836 290 893 857 .. + // 158 869 206 504 799 758 431 580 780 788 583 641 32 653 .. + // 252 709 129 368 440 314 287 854 460 594 512 239 719 751 .. + // 708 670 269 832 137 356 960 651 398 893 407 477 552 805 881 850; + // //Constraint 3 + // 806 361 199 781 596 669 957 358 259 888 319 751 275 177 .. + // 883 749 229 265 282 694 819 77 190 551 140 442 867 283 .. + // 137 359 445 58 440 192 485 744 844 969 50 833 57 877 .. + // 482 732 968 113 486 710 439 747 174 260 877 474 841 422 .. + // 280 684 330 910 791 322 404 403 519 148 948 414 894 147 .. + // 73 297 97 651 380 67 582 973 143 732 624 518 847 113 .. + // 382 97 905 398 859 4 142 110 11 213 398 173 106 331 254 447 ; + // //Constraint 4 + // 404 197 817 1000 44 307 39 659 46 334 448 599 931 776 .. + // 263 980 807 378 278 841 700 210 542 636 388 129 203 110 .. + // 817 502 657 804 662 989 585 645 113 436 610 948 919 115 .. + // 967 13 445 449 740 592 327 167 368 335 179 909 825 614 .. + // 987 350 179 415 821 525 774 283 427 275 659 392 73 896 .. + // 68 982 697 421 246 672 649 731 191 514 983 886 95 846 .. + // 689 206 417 14 735 267 822 977 302 687 118 990 323 993 525 322; + // //Constrain 5 + // 475 36 287 577 45 700 803 654 196 844 657 387 518 143 .. + // 515 335 942 701 332 803 265 922 908 139 995 845 487 100 .. + // 447 653 649 738 424 475 425 926 795 47 136 801 904 740 .. + // 768 460 76 660 500 915 897 25 716 557 72 696 653 933 .. + // 420 582 810 861 758 647 237 631 271 91 75 756 409 440 .. + // 483 336 765 637 981 980 202 35 594 689 602 76 767 693 .. + // 893 160 785 311 417 748 375 362 617 553 474 915 457 261 350 635 ; + // ]; + // nbCon = size(conMatrix,1) + // nbVar = size(conMatrix,2) + // // Lower Bound of variables + // lb = repmat(0,1,nbVar) + // // Upper Bound of variables + // ub = repmat(1,1,nbVar) + // // Row Matrix for telling symphony that the is integer or not + // isInt = repmat(%t,1,nbVar) + // // Lower Bound of constrains + // conLB=repmat(0,nbCon,1); + // // Upper Bound of constraints + // conUB=[11927 13727 11551 13056 13460 ]'; + // options = ["time_limit" "25"] + // // The expected solution : + // // Output variables + // xopt = [0 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 0 1 .. + // 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 1 0 .. + // 0 1 0 1 0 0 1 0 0 1 0 1 0 0 0 0 0 1 1 0 0 0 0 0 1 1 0 0 1 0 0 1 0] + // // Optimal value + // fopt = [ 24381 ] + // // Calling Symphony + // [x,f,status,output] = symphony(nbVar,nbCon,p,isInt,lb,ub,conMatrix,conLB,conUB,-1,options) + // + // Authors + // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh + +//To check the number of input and output argument + [lhs , rhs] = argn(); + +//To check the number of argument given by user + if ( rhs < 9 | rhs > 11 ) then + errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be in the set [9 10 11]"), "Symphony", rhs); + error(errmsg) + end + + nbVar = varargin(1); + nbCon = varargin(2); + objCoef = varargin(3); + isInt = varargin(4); + LB = varargin(5); + UB = varargin(6); + conMatrix = varargin(7); + conLB = varargin(8); + conUB = varargin(9); + + if ( rhs<10 ) then + objSense = 1; + else + objSense = varargin(10); + end + + if (rhs<11) then + options = list(); + else + options = varargin(11); + end + + +//Check the size of constraint which should equal to the number of constraints + if ( size(conMatrix,1) ~= nbCon) then + errmsg = msprintf(gettext("%s: The Lower Bound is not equal to the number of variables"), "Symphony"); + error(errmsg); + end + +//Check the size of Lower Bound which should equal to the number of variables + if ( size(LB,2) ~= nbVar) then + errmsg = msprintf(gettext("%s: The Lower Bound is not equal to the number of variables"), "Symphony"); + error(errmsg); + end + +//Check the size of Upper Bound which should equal to the number of variables + if ( size(UB,2) ~= nbVar) then + errmsg = msprintf(gettext("%s: The Upper Bound is not equal to the number of variables"), "Symphony"); + error(errmsg); + end + +//Check the size of constraints of Lower Bound which should equal to the number of constraints + if ( size(conLB,1) ~= nbCon) then + errmsg = msprintf(gettext("%s: The Lower Bound of constraints is not equal to the number of constraints"), "Symphony"); + error(errmsg); + end + +//Check the size of constraints of Upper Bound which should equal to the number of constraints + if ( size(conUB,1) ~= nbCon) then + errmsg = msprintf(gettext("%s: The Upper Bound of constraints is not equal to the number of constraints"), "Symphony"); + error(errmsg); + end + + [xopt,fopt,status,output] = symphony_call(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB,objSense,options); + +endfunction diff --git a/macros/symphony_call.bin b/macros/symphony_call.bin index b95e887..5008236 100644 Binary files a/macros/symphony_call.bin and b/macros/symphony_call.bin differ diff --git a/macros/symphony_call.sci b/macros/symphony_call.sci index ea5f34f..c8323fc 100644 --- a/macros/symphony_call.sci +++ b/macros/symphony_call.sci @@ -16,7 +16,7 @@ function [xopt,fopt,status,output] = symphony_call(nbVar,nbCon,objCoef,isInt,LB, //Setting Options for the Symphpony setOptions(options); - + //Choosing to launch basic or advanced version if(~issparse(conMatrix)) then sym_loadProblemBasic(nbVar,nbCon,LB,UB,objCoef,isInt,objSense,conMatrix,conLB,conUB); @@ -26,8 +26,8 @@ function [xopt,fopt,status,output] = symphony_call(nbVar,nbCon,objCoef,isInt,LB, sym_loadProblem(nbVar,nbCon,LB,UB,objCoef,isInt,objSense,conMatrix_advanced,conLB,conUB); end - op = sym_solve(); + disp(op); xopt = []; fopt = []; diff --git a/macros/symphony_call.sci~ b/macros/symphony_call.sci~ new file mode 100644 index 0000000..057ba63 --- /dev/null +++ b/macros/symphony_call.sci~ @@ -0,0 +1,52 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// Author: Harpreet Singh +// Organization: FOSSEE, IIT Bombay +// Email: harpreet.mertia@gmail.com +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt + +function [xopt,fopt,status,output] = symphony_call(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB,objSense,options) + + //Opening Symphony environment + sym_open(); + + //Setting Options for the Symphpony +// setOptions(options); + + //Choosing to launch basic or advanced version + if(~issparse(conMatrix)) then + sym_loadProblemBasic(nbVar,nbCon,LB,UB,objCoef,isInt,objSense,conMatrix,conLB,conUB); + else + // Changing to Constraint Matrix into sparse matrix + conMatrix_advanced=sparse(conMatrix); + sym_loadProblem(nbVar,nbCon,LB,UB,objCoef,isInt,objSense,conMatrix_advanced,conLB,conUB); + end + + op = sym_solve(); + disp(op); + + xopt = []; + fopt = []; + status = []; + output = []; + + if (~op) then + xopt = sym_getVarSoln(); + // Symphony gives a row matrix converting it to column matrix + xopt = xopt'; + + fopt = sym_getObjVal(); + end + + status = sym_getStatus(); + + output = struct("Iterations" , []); + + output.Iterations = sym_getIterCount(); + + +endfunction diff --git a/macros/symphonymat.bin b/macros/symphonymat.bin new file mode 100644 index 0000000..5089973 Binary files /dev/null and b/macros/symphonymat.bin differ diff --git a/macros/symphonymat.sci b/macros/symphonymat.sci new file mode 100644 index 0000000..ef70b7c --- /dev/null +++ b/macros/symphonymat.sci @@ -0,0 +1,242 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// Author: Harpreet Singh +// Organization: FOSSEE, IIT Bombay +// Email: harpreet.mertia@gmail.com +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt + +function [xopt,fopt,status,iter] = symphonymat (varargin) + // Solves a mixed integer linear programming constrained optimization problem in intlinprog format. + // + // Calling Sequence + // xopt = symphonymat(f,intcon,A,b) + // xopt = symphonymat(f,intcon,A,b,Aeq,beq) + // xopt = symphonymat(f,intcon,A,b,Aeq,beq,lb,ub) + // xopt = symphonymat(f,intcon,A,b,Aeq,beq,lb,ub,options) + // [xopt,fopt,status,output] = symphonymat( ... ) + // + // Parameters + // f : a 1xn matrix of doubles, where n is number of variables, contains coefficients of the variables in the objective + // intcon : Vector of integer constraints, specified as a vector of positive integers. The values in intcon indicate the components of the decision variable x that are integer-valued. intcon has values from 1 through number of variable + // A : Linear inequality constraint matrix, specified as a matrix of doubles. A represents the linear coefficients in the constraints A*x ≤ b. A has size M-by-N, where M is the number of constraints and N is number of variables + // b : Linear inequality constraint vector, specified as a vector of doubles. b represents the constant vector in the constraints A*x ≤ b. b has length M, where A is M-by-N + // Aeq : Linear equality constraint matrix, specified as a matrix of doubles. Aeq represents the linear coefficients in the constraints Aeq*x = beq. Aeq has size Meq-by-N, where Meq is the number of constraints and N is number of variables + // beq : Linear equality constraint vector, specified as a vector of doubles. beq represents the constant vector in the constraints Aeq*x = beq. beq has length Meq, where Aeq is Meq-by-N. + // lb : Lower bounds, specified as a vector or array of doubles. lb represents the lower bounds elementwise in lb ≤ x ≤ ub. + // ub : Upper bounds, specified as a vector or array of doubles. ub represents the upper bounds elementwise in lb ≤ x ≤ ub. + // options : a list containing the the parameters to be set. + // xopt : a 1xn matrix of doubles, the computed solution of the optimization problem + // fopt : a 1x1 matrix of doubles, the function value at x + // output : The output data structure contains detailed informations about the optimization process. + // + // Description + // Search the minimum or maximum of a constrained mixed integer linear programming optimization problem specified by : + // find the minimum or maximum of f(x) such that + // + // + // \begin{eqnarray} + // &\mbox{min}_{x} + // & f(x) \\ + // & \text{subject to} & conLB \leq C(x) \leq conUB \\ + // & & lb \leq x \leq ub \\ + // \end{eqnarray} + // + // + // We are calling SYMPHONY written in C by gateway files for the actual computation. SYMPHONY was originally written by ​Ted Ralphs, ​Menal Guzelsoy and ​Ashutosh Mahajan. + // + // Examples + // // Objective function + // c = [350*5,330*3,310*4,280*6,500,450,400,100] + // // Lower Bound of variable + // lb = repmat(0,1,8); + // // Upper Bound of variables + // ub = [repmat(1,1,4) repmat(%inf,1,4)]; + // // Constraint Matrix + // Aeq = [5,3,4,6,1,1,1,1; + // 5*0.05,3*0.04,4*0.05,6*0.03,0.08,0.07,0.06,0.03; + // 5*0.03,3*0.03,4*0.04,6*0.04,0.06,0.07,0.08,0.09;] + // beq = [ 25, 1.25, 1.25] + // intcon = [1 2 3 4]; + // // Calling Symphony + // [x,f,status,output] = symphonymat(c,intcon,[],[],Aeq,beq,lb,ub) + // + // Examples + // // An advanced case where we set some options in symphony + // // This problem is taken from + // // P.C.Chu and J.E.Beasley + // // "A genetic algorithm for the multidimensional knapsack problem", + // // Journal of Heuristics, vol. 4, 1998, pp63-86. + // // The problem to be solved is: + // // Max sum{j=1,...,n} p(j)x(j) + // // st sum{j=1,...,n} r(i,j)x(j) <= b(i) i=1,...,m + // // x(j)=0 or 1 + // // The function to be maximize i.e. P(j) + // objCoef = -1*[ 504 803 667 1103 834 585 811 856 690 832 846 813 868 793 .. + // 825 1002 860 615 540 797 616 660 707 866 647 746 1006 608 .. + // 877 900 573 788 484 853 942 630 591 630 640 1169 932 1034 .. + // 957 798 669 625 467 1051 552 717 654 388 559 555 1104 783 .. + // 959 668 507 855 986 831 821 825 868 852 832 828 799 686 .. + // 510 671 575 740 510 675 996 636 826 1022 1140 654 909 799 .. + // 1162 653 814 625 599 476 767 954 906 904 649 873 565 853 1008 632] + // //Constraint Matrix + // conMatrix = [ //Constraint 1 + // 42 41 523 215 819 551 69 193 582 375 367 478 162 898 .. + // 550 553 298 577 493 183 260 224 852 394 958 282 402 604 .. + // 164 308 218 61 273 772 191 117 276 877 415 873 902 465 .. + // 320 870 244 781 86 622 665 155 680 101 665 227 597 354 .. + // 597 79 162 998 849 136 112 751 735 884 71 449 266 420 .. + // 797 945 746 46 44 545 882 72 383 714 987 183 731 301 .. + // 718 91 109 567 708 507 983 808 766 615 554 282 995 946 651 298; + // //Constraint 2 + // 509 883 229 569 706 639 114 727 491 481 681 948 687 941 .. + // 350 253 573 40 124 384 660 951 739 329 146 593 658 816 .. + // 638 717 779 289 430 851 937 289 159 260 930 248 656 833 .. + // 892 60 278 741 297 967 86 249 354 614 836 290 893 857 .. + // 158 869 206 504 799 758 431 580 780 788 583 641 32 653 .. + // 252 709 129 368 440 314 287 854 460 594 512 239 719 751 .. + // 708 670 269 832 137 356 960 651 398 893 407 477 552 805 881 850; + // //Constraint 3 + // 806 361 199 781 596 669 957 358 259 888 319 751 275 177 .. + // 883 749 229 265 282 694 819 77 190 551 140 442 867 283 .. + // 137 359 445 58 440 192 485 744 844 969 50 833 57 877 .. + // 482 732 968 113 486 710 439 747 174 260 877 474 841 422 .. + // 280 684 330 910 791 322 404 403 519 148 948 414 894 147 .. + // 73 297 97 651 380 67 582 973 143 732 624 518 847 113 .. + // 382 97 905 398 859 4 142 110 11 213 398 173 106 331 254 447 ; + // //Constraint 4 + // 404 197 817 1000 44 307 39 659 46 334 448 599 931 776 .. + // 263 980 807 378 278 841 700 210 542 636 388 129 203 110 .. + // 817 502 657 804 662 989 585 645 113 436 610 948 919 115 .. + // 967 13 445 449 740 592 327 167 368 335 179 909 825 614 .. + // 987 350 179 415 821 525 774 283 427 275 659 392 73 896 .. + // 68 982 697 421 246 672 649 731 191 514 983 886 95 846 .. + // 689 206 417 14 735 267 822 977 302 687 118 990 323 993 525 322; + // //Constrain 5 + // 475 36 287 577 45 700 803 654 196 844 657 387 518 143 .. + // 515 335 942 701 332 803 265 922 908 139 995 845 487 100 .. + // 447 653 649 738 424 475 425 926 795 47 136 801 904 740 .. + // 768 460 76 660 500 915 897 25 716 557 72 696 653 933 .. + // 420 582 810 861 758 647 237 631 271 91 75 756 409 440 .. + // 483 336 765 637 981 980 202 35 594 689 602 76 767 693 .. + // 893 160 785 311 417 748 375 362 617 553 474 915 457 261 350 635 ; + // ]; + // nbVar = size(objCoef,2) + // conUB=[11927 13727 11551 13056 13460 ]; + // // Lower Bound of variables + // lb = repmat(0,1,nbVar) + // // Upper Bound of variables + // ub = repmat(1,1,nbVar) + // // Lower Bound of constrains + // intcon = [] + // for i = 1:nbVar + // intcon = [intcon i]; + // end + // options = list("time_limit", 25); + // // The expected solution : + // // Output variables + // xopt = [0 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 0 1 .. + // 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 1 .. + // 0 0 1 0 0 1 0 1 0 0 1 0 0 1 0 1 0 0 0 0 0 1 1 0 0 0 0 0 1 1 0 0 1 0 0 1 0] + // // Optimal value + // fopt = [ 24381 ] + // // Calling Symphony + // [x,f,status,output] = symphonymat(objCoef,intcon,conMatrix,conUB,[],[],lb,ub,options); + // + // Authors + // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh + + +//To check the number of input and output argument + [lhs , rhs] = argn(); + +//To check the number of argument given by user + if ( rhs < 4 | rhs == 5 | rhs == 7 | rhs > 9 ) then + errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be in the set [4 6 8 9]"), "Symphony", rhs); + error(errmsg) + end + + + objCoef = varargin(1) + intcon = varargin(2) + A = varargin(3) + b = varargin(4) + + nbVar = size(objCoef,2); + nbCon = size(A,1); + + if ( rhs<4 ) then + Aeq = [] + beq = [] + else + Aeq = varargin(5); + beq = varargin(6); + + if (size(Aeq,1)~=0) then + //Check the size of equality constraint which should equal to the number of inequality constraints + if ( size(Aeq,2) ~= nbVar) then + errmsg = msprintf(gettext("%s: The size of equality constraint is not equal to the number of variables"), "Symphony"); + error(errmsg); + end + + //Check the size of upper bound of inequality constraint which should equal to the number of constraints + if ( size(beq,2) ~= size(Aeq,1)) then + errmsg = msprintf(gettext("%s: The equality constraint upper bound is not equal to the number of equality constraint"), "Symphony"); + error(errmsg); + end + end + + end + + if ( rhs<6 ) then + lb = repmat(-%inf,1,nbVar); + ub = repmat(%inf,1,nbVar); + else + lb = varargin(7); + ub = varargin(8); + end + + if (rhs<9) then + options = list(); + else + options = varargin(9); + end + + +//Check the size of lower bound of inequality constraint which should equal to the number of constraints + if ( size(b,2) ~= size(A,1)) then + errmsg = msprintf(gettext("%s: The Lower Bound of inequality constraint is not equal to the number of constraint"), "Symphony"); + error(errmsg); + end + +//Check the size of Lower Bound which should equal to the number of variables + if ( size(lb,2) ~= nbVar) then + errmsg = msprintf(gettext("%s: The Lower Bound is not equal to the number of variables"), "Symphony"); + error(errmsg); + end + +//Check the size of Upper Bound which should equal to the number of variables + if ( size(ub,2) ~= nbVar) then + errmsg = msprintf(gettext("%s: The Upper Bound is not equal to the number of variables"), "Symphony"); + error(errmsg); + end + + //Changing the inputs in symphony's format + conMatrix = [A;Aeq] + nbCon = size(conMatrix,1); + conLB = [repmat(-%inf,1,size(A,1)), beq]'; + conUB = [b,beq]' ; + + isInt = repmat(%f,1,nbVar); + for i=1:size(intcon,2) + isInt(intcon(i)) = %t + end + + objSense = 1; + + [xopt,fopt,status,iter] = symphony_call(nbVar,nbCon,objCoef,isInt,lb,ub,conMatrix,conLB,conUB,objSense,options); + +endfunction diff --git a/macros/symphonymat.sci~ b/macros/symphonymat.sci~ new file mode 100644 index 0000000..455dd67 --- /dev/null +++ b/macros/symphonymat.sci~ @@ -0,0 +1,242 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// Author: Harpreet Singh +// Organization: FOSSEE, IIT Bombay +// Email: harpreet.mertia@gmail.com +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt + +function [xopt,fopt,status,iter] = symphonymat (varargin) + // Solves a mixed integer linear programming constrained optimization problem in intlinprog format. + // + // Calling Sequence + // xopt = symphonymat(f,intcon,A,b) + // xopt = symphonymat(f,intcon,A,b,Aeq,beq) + // xopt = symphonymat(f,intcon,A,b,Aeq,beq,lb,ub) + // xopt = symphonymat(f,intcon,A,b,Aeq,beq,lb,ub,options) + // [xopt,fopt,status,output] = symphonymat( ... ) + // + // Parameters + // f : a 1xn matrix of doubles, where n is number of variables, contains coefficients of the variables in the objective + // intcon : Vector of integer constraints, specified as a vector of positive integers. The values in intcon indicate the components of the decision variable x that are integer-valued. intcon has values from 1 through number of variable + // A : Linear inequality constraint matrix, specified as a matrix of doubles. A represents the linear coefficients in the constraints A*x ≤ b. A has size M-by-N, where M is the number of constraints and N is number of variables + // b : Linear inequality constraint vector, specified as a vector of doubles. b represents the constant vector in the constraints A*x ≤ b. b has length M, where A is M-by-N + // Aeq : Linear equality constraint matrix, specified as a matrix of doubles. Aeq represents the linear coefficients in the constraints Aeq*x = beq. Aeq has size Meq-by-N, where Meq is the number of constraints and N is number of variables + // beq : Linear equality constraint vector, specified as a vector of doubles. beq represents the constant vector in the constraints Aeq*x = beq. beq has length Meq, where Aeq is Meq-by-N. + // lb : Lower bounds, specified as a vector or array of doubles. lb represents the lower bounds elementwise in lb ≤ x ≤ ub. + // ub : Upper bounds, specified as a vector or array of doubles. ub represents the upper bounds elementwise in lb ≤ x ≤ ub. + // options : a list containing the the parameters to be set. + // xopt : a 1xn matrix of doubles, the computed solution of the optimization problem + // fopt : a 1x1 matrix of doubles, the function value at x + // output : The output data structure contains detailed informations about the optimization process. + // + // Description + // Search the minimum or maximum of a constrained mixed integer linear programming optimization problem specified by : + // find the minimum or maximum of f(x) such that + // + // + // \begin{eqnarray} + // &\mbox{min}_{x} + // & f(x) \\ + // & \text{subject to} & conLB \leq C(x) \leq conUB \\ + // & & lb \leq x \leq ub \\ + // \end{eqnarray} + // + // + // We are calling SYMPHONY written in C by gateway files for the actual computation. SYMPHONY was originally written by ​Ted Ralphs, ​Menal Guzelsoy and ​Ashutosh Mahajan. + // + // Examples + // // Objective function + // c = [350*5,330*3,310*4,280*6,500,450,400,100] + // // Lower Bound of variable + // lb = repmat(0,1,8); + // // Upper Bound of variables + // ub = [repmat(1,1,4) repmat(%inf,1,4)]; + // // Constraint Matrix + // Aeq = [5,3,4,6,1,1,1,1; + // 5*0.05,3*0.04,4*0.05,6*0.03,0.08,0.07,0.06,0.03; + // 5*0.03,3*0.03,4*0.04,6*0.04,0.06,0.07,0.08,0.09;] + // beq = [ 25, 1.25, 1.25] + // intcon = [1 2 3 4]; + // // Calling Symphony + // [x,f,status,output] = symphonymat(c,intcon,[],[],Aeq,beq,lb,ub) + // + // Examples + // // An advanced case where we set some options in symphony + // // This problem is taken from + // // P.C.Chu and J.E.Beasley + // // "A genetic algorithm for the multidimensional knapsack problem", + // // Journal of Heuristics, vol. 4, 1998, pp63-86. + // // The problem to be solved is: + // // Max sum{j=1,...,n} p(j)x(j) + // // st sum{j=1,...,n} r(i,j)x(j) <= b(i) i=1,...,m + // // x(j)=0 or 1 + // // The function to be maximize i.e. P(j) + // objCoef = -1*[ 504 803 667 1103 834 585 811 856 690 832 846 813 868 793 .. + // 825 1002 860 615 540 797 616 660 707 866 647 746 1006 608 .. + // 877 900 573 788 484 853 942 630 591 630 640 1169 932 1034 .. + // 957 798 669 625 467 1051 552 717 654 388 559 555 1104 783 .. + // 959 668 507 855 986 831 821 825 868 852 832 828 799 686 .. + // 510 671 575 740 510 675 996 636 826 1022 1140 654 909 799 .. + // 1162 653 814 625 599 476 767 954 906 904 649 873 565 853 1008 632] + // //Constraint Matrix + // conMatrix = [ //Constraint 1 + // 42 41 523 215 819 551 69 193 582 375 367 478 162 898 .. + // 550 553 298 577 493 183 260 224 852 394 958 282 402 604 .. + // 164 308 218 61 273 772 191 117 276 877 415 873 902 465 .. + // 320 870 244 781 86 622 665 155 680 101 665 227 597 354 .. + // 597 79 162 998 849 136 112 751 735 884 71 449 266 420 .. + // 797 945 746 46 44 545 882 72 383 714 987 183 731 301 .. + // 718 91 109 567 708 507 983 808 766 615 554 282 995 946 651 298; + // //Constraint 2 + // 509 883 229 569 706 639 114 727 491 481 681 948 687 941 .. + // 350 253 573 40 124 384 660 951 739 329 146 593 658 816 .. + // 638 717 779 289 430 851 937 289 159 260 930 248 656 833 .. + // 892 60 278 741 297 967 86 249 354 614 836 290 893 857 .. + // 158 869 206 504 799 758 431 580 780 788 583 641 32 653 .. + // 252 709 129 368 440 314 287 854 460 594 512 239 719 751 .. + // 708 670 269 832 137 356 960 651 398 893 407 477 552 805 881 850; + // //Constraint 3 + // 806 361 199 781 596 669 957 358 259 888 319 751 275 177 .. + // 883 749 229 265 282 694 819 77 190 551 140 442 867 283 .. + // 137 359 445 58 440 192 485 744 844 969 50 833 57 877 .. + // 482 732 968 113 486 710 439 747 174 260 877 474 841 422 .. + // 280 684 330 910 791 322 404 403 519 148 948 414 894 147 .. + // 73 297 97 651 380 67 582 973 143 732 624 518 847 113 .. + // 382 97 905 398 859 4 142 110 11 213 398 173 106 331 254 447 ; + // //Constraint 4 + // 404 197 817 1000 44 307 39 659 46 334 448 599 931 776 .. + // 263 980 807 378 278 841 700 210 542 636 388 129 203 110 .. + // 817 502 657 804 662 989 585 645 113 436 610 948 919 115 .. + // 967 13 445 449 740 592 327 167 368 335 179 909 825 614 .. + // 987 350 179 415 821 525 774 283 427 275 659 392 73 896 .. + // 68 982 697 421 246 672 649 731 191 514 983 886 95 846 .. + // 689 206 417 14 735 267 822 977 302 687 118 990 323 993 525 322; + // //Constrain 5 + // 475 36 287 577 45 700 803 654 196 844 657 387 518 143 .. + // 515 335 942 701 332 803 265 922 908 139 995 845 487 100 .. + // 447 653 649 738 424 475 425 926 795 47 136 801 904 740 .. + // 768 460 76 660 500 915 897 25 716 557 72 696 653 933 .. + // 420 582 810 861 758 647 237 631 271 91 75 756 409 440 .. + // 483 336 765 637 981 980 202 35 594 689 602 76 767 693 .. + // 893 160 785 311 417 748 375 362 617 553 474 915 457 261 350 635 ; + // ]; + // nbVar = size(objCoef,2) + // conUB=[11927 13727 11551 13056 13460 ]; + // // Lower Bound of variables + // lb = repmat(0,1,nbVar) + // // Upper Bound of variables + // ub = repmat(1,1,nbVar) + // // Lower Bound of constrains + // intcon = [] + // for i = 1:nbVar + // intcon = [intcon i]; + // end + // options = list("time_limit", 25); + // // The expected solution : + // // Output variables + // xopt = [0 1 1 0 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 1 1 0 1 .. + // 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 1 1 .. + // 0 0 1 0 0 1 0 1 0 0 1 0 0 1 0 1 0 0 0 0 0 1 1 0 0 0 0 0 1 1 0 0 1 0 0 1 0] + // // Optimal value + // fopt = [ 24381 ] + // // Calling Symphony + // [x,f,status,output] = symphonymat(objCoef,intcon,conMatrix,conUB,[],[],lb,ub,options); + // + // Authors + // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh + + +//To check the number of input and output argument + [lhs , rhs] = argn(); + +//To check the number of argument given by user + if ( rhs < 4 | rhs == 5 | rhs == 7 | rhs > 9 ) then + errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be in the set [4 6 8 9]"), "Symphony", rhs); + error(errmsg) + end + + + objCoef = varargin(1) + intcon = varargin(2) + A = varargin(3) + b = varargin(4) + + nbVar = size(objCoef,2); + nbCon = size(A,1); + + if ( rhs<4 ) then + Aeq = [] + beq = [] + else + Aeq = varargin(5); + beq = varargin(6); + + if (size(Aeq,1)~=0) then + //Check the size of equality constraint which should equal to the number of inequality constraints + if ( size(Aeq,2) ~= nbVar) then + errmsg = msprintf(gettext("%s: The size of equality constraint is not equal to the number of variables"), "Symphony"); + error(errmsg); + end + + //Check the size of upper bound of inequality constraint which should equal to the number of constraints + if ( size(beq,2) ~= size(Aeq,1)) then + errmsg = msprintf(gettext("%s: The equality constraint upper bound is not equal to the number of equality constraint"), "Symphony"); + error(errmsg); + end + end + + end + + if ( rhs<6 ) then + lb = repmat(-%inf,1,nbVar); + ub = repmat(%inf,1,nbVar); + else + lb = varargin(7); + ub = varargin(8); + end + + if (rhs<8) then + options = list(); + else + options = varargin(9); + end + + +//Check the size of lower bound of inequality constraint which should equal to the number of constraints + if ( size(b,2) ~= size(A,1)) then + errmsg = msprintf(gettext("%s: The Lower Bound of inequality constraint is not equal to the number of constraint"), "Symphony"); + error(errmsg); + end + +//Check the size of Lower Bound which should equal to the number of variables + if ( size(lb,2) ~= nbVar) then + errmsg = msprintf(gettext("%s: The Lower Bound is not equal to the number of variables"), "Symphony"); + error(errmsg); + end + +//Check the size of Upper Bound which should equal to the number of variables + if ( size(ub,2) ~= nbVar) then + errmsg = msprintf(gettext("%s: The Upper Bound is not equal to the number of variables"), "Symphony"); + error(errmsg); + end + + //Changing the inputs in symphony's format + conMatrix = [A;Aeq] + nbCon = size(conMatrix,1); + conLB = [repmat(-%inf,1,size(A,1)), beq]'; + conUB = [b,beq]' ; + + isInt = repmat(%f,1,nbVar); + for i=1:size(intcon,2) + isInt(intcon(i)) = %t + end + + objSense = 1; + + [xopt,fopt,status,iter] = symphony_call(nbVar,nbCon,objCoef,isInt,lb,ub,conMatrix,conLB,conUB,objSense,options); + +endfunction diff --git a/sci_gateway/cpp/README.rst b/sci_gateway/cpp/README.rst new file mode 100644 index 0000000..3348354 --- /dev/null +++ b/sci_gateway/cpp/README.rst @@ -0,0 +1,49 @@ +SCILAB GATEWAY +============== + +It is used to call the native functions written in C to scilab. + +List of Files +============= + +Symphony +-------- + +List of files used for symphony: + +1. globals.cpp +2. sci_solver_status_query_functions.cpp +3. sci_sym_addrowcal.cpp +4. sci_sym_getinfinity.cpp +5. sci_sym_getobjsense.cpp +6. sci_sym_getrowact.cpp +7. sci_sym_isenactive.cpp +8. sci_sym_load_mps.cpp +9. sci_sym_loadproblem.cpp +10. sci_sym_openclose.cpp +11. sci_sym_primalbound.cpp +12. sci_sym_remove.cpp +13. sci_sym_rowmod.cpp +14. sci_sym_setcolsoln.cpp +15. sci_sym_set_indices.cpp +16. sci_sym_setobj.cpp +17. sci_sym_set_variables.cpp +18. sci_sym_solution.cpp +19. sci_sym_solve.cpp +20. sci_sym_varbounds.cpp +21. sci_vartype.cpp +22. sym_data_query_functions.cpp +23. sci_iofunc.cpp +24. sci_iofunc.hpp + +qpipopt +------- + +List of files used for qpipopt: + +1. sci_iofunc.cpp +2. sci_iofunc.hpp +3. QuadNLP.hpp +4. sci_ipopt.cpp +5. sci_QuadNLP.cpp + diff --git a/sci_gateway/cpp/README.rst~ b/sci_gateway/cpp/README.rst~ new file mode 100644 index 0000000..e69de29 diff --git a/sci_gateway/cpp/builder_gateway_cpp.sce b/sci_gateway/cpp/builder_gateway_cpp.sce index b42ac8e..225edd8 100644 --- a/sci_gateway/cpp/builder_gateway_cpp.sce +++ b/sci_gateway/cpp/builder_gateway_cpp.sce @@ -12,7 +12,7 @@ mode(-1) lines(0) -toolbox_title = "FAMOS" +toolbox_title = "FAMOS"; [a, opt] = getversion(); Version = opt(2); @@ -138,8 +138,8 @@ Files = [ "sci_sym_getrowact.cpp", "sci_sym_getobjsense.cpp", "sci_sym_remove.cpp", - "sci_QuadNLP.cpp" - "QuadNLP.hpp" + "sci_QuadNLP.cpp", + "QuadNLP.hpp", "sci_ipopt.cpp" ] diff --git a/sci_gateway/cpp/builder_gateway_cpp.sce~ b/sci_gateway/cpp/builder_gateway_cpp.sce~ new file mode 100644 index 0000000..225edd8 --- /dev/null +++ b/sci_gateway/cpp/builder_gateway_cpp.sce~ @@ -0,0 +1,149 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// Author: Keyur Joshi, Sai Kiran, Iswarya and Harpreet Singh +// Organization: FOSSEE, IIT Bombay +// Email: harpreet.mertia@gmail.com +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt + +mode(-1) +lines(0) + +toolbox_title = "FAMOS"; + +[a, opt] = getversion(); +Version = opt(2); + +path_builder = get_absolute_file_path('builder_gateway_cpp.sce'); + +tools_path = path_builder + "../../thirdparty/linux/"; + +C_Flags=["-w -fpermissive -I"+tools_path+"include/coin -Wl,-rpath="+tools_path+"lib/"+Version+filesep()+" "] + +Linker_Flag = ["-L"+tools_path+"lib/"+Version+filesep()+"libSym"+" "+"-L"+tools_path+"lib/"+Version+filesep()+"libipopt" ] + + +//Name of All the Functions +Function_Names = [ + //for opening/closing environment and checking if it is open/close + "sym_open","sci_sym_open"; + "sym_close","sci_sym_close"; + "sym_isEnvActive","sci_sym_isEnvActive"; + + //run time parameters + "sym_resetParams","sci_sym_set_defaults"; + "sym_setIntParam","sci_sym_set_int_param"; + "sym_getIntParam","sci_sym_get_int_param"; + "sym_setDblParam","sci_sym_set_dbl_param"; + "sym_getDblParam","sci_sym_get_dbl_param"; + "sym_setStrParam","sci_sym_set_str_param"; + "sym_getStrParam","sci_sym_get_str_param"; + "sym_getInfinity","sci_sym_getInfinity"; + + //problem loaders + "sym_loadProblemBasic","sci_sym_loadProblemBasic"; + "sym_loadProblem","sci_sym_loadProblem"; + "sym_loadMPS","sci_sym_load_mps"; + + //basic data + "sym_getNumConstr","sci_sym_get_num_int"; + "sym_getNumVar","sci_sym_get_num_int"; + "sym_getNumElements","sci_sym_get_num_int"; + + //variable and objective data + "sym_isContinuous","sci_sym_isContinuous"; + "sym_isBinary","sci_sym_isBinary"; + "sym_isInteger","sci_sym_isInteger"; + "sym_setContinuous","sci_sym_set_continuous"; + "sym_setInteger","sci_sym_set_integer"; + "sym_getVarLower","sci_sym_get_dbl_arr"; + "sym_getVarUpper","sci_sym_get_dbl_arr"; + "sym_setVarLower","sci_sym_setVarBound"; + "sym_setVarUpper","sci_sym_setVarBound"; + "sym_getObjCoeff","sci_sym_get_dbl_arr"; + "sym_setObjCoeff","sci_sym_setObjCoeff"; + "sym_getObjSense","sci_sym_getObjSense"; + "sym_setObjSense","sci_sym_setObjSense"; + + //constraint data + "sym_getRhs","sci_sym_get_dbl_arr"; + "sym_getConstrRange","sci_sym_get_dbl_arr"; + "sym_getConstrLower","sci_sym_get_dbl_arr"; + "sym_getConstrUpper","sci_sym_get_dbl_arr"; + "sym_setConstrLower","sci_sym_setConstrBound"; + "sym_setConstrUpper","sci_sym_setConstrBound"; + "sym_setConstrType","sci_sym_setConstrType"; + "sym_getMatrix","sci_sym_get_matrix"; + "sym_getConstrSense","sci_sym_get_row_sense"; + + //add/remove variables and constraints + "sym_addConstr","sci_sym_addConstr"; + "sym_addVar","sci_sym_addVar"; + "sym_deleteVars","sci_sym_delete_cols"; + "sym_deleteConstrs","sci_sym_delete_rows"; + + //primal bound + "sym_getPrimalBound","sci_sym_getPrimalBound"; + "sym_setPrimalBound","sci_sym_setPrimalBound"; + + //set preliminary solution + "sym_setVarSoln","sci_sym_setColSoln"; + + //solve + "sym_solve","sci_sym_solve"; + + //post solve functions + "sym_getStatus","sci_sym_get_status"; + "sym_isOptimal","sci_sym_get_solver_status"; + "sym_isInfeasible","sci_sym_get_solver_status"; + "sym_isAbandoned","sci_sym_get_solver_status"; + "sym_isIterLimitReached","sci_sym_get_solver_status"; + "sym_isTimeLimitReached","sci_sym_get_solver_status"; + "sym_isTargetGapAchieved","sci_sym_get_solver_status"; + "sym_getVarSoln","sci_sym_getVarSoln"; + "sym_getObjVal","sci_sym_getObjVal"; + "sym_getIterCount","sci_sym_get_iteration_count"; + "sym_getConstrActivity","sci_sym_getRowActivity"; + + //QP function + "solveqp","sci_solveqp" + ]; + +//Name of all the files to be compiled +Files = [ + "globals.cpp", + "sci_iofunc.hpp", + "sci_iofunc.cpp", + "sci_sym_openclose.cpp", + "sci_solver_status_query_functions.cpp", + "sci_sym_solve.cpp", + "sci_sym_loadproblem.cpp", + "sci_sym_isenvactive.cpp", + "sci_sym_load_mps.cpp", + "sci_vartype.cpp", + "sci_sym_getinfinity.cpp", + "sci_sym_solution.cpp", + "sym_data_query_functions.cpp" + "sci_sym_set_variables.cpp", + "sci_sym_setobj.cpp", + "sci_sym_varbounds.cpp", + "sci_sym_rowmod.cpp", + "sci_sym_set_indices.cpp", + "sci_sym_addrowcol.cpp", + "sci_sym_primalbound.cpp", + "sci_sym_setcolsoln.cpp", + "sci_sym_getrowact.cpp", + "sci_sym_getobjsense.cpp", + "sci_sym_remove.cpp", + "sci_QuadNLP.cpp", + "QuadNLP.hpp", + "sci_ipopt.cpp" + + ] + +tbx_build_gateway(toolbox_title,Function_Names,Files,get_absolute_file_path("builder_gateway_cpp.sce"), [], Linker_Flag, C_Flags, [], "g++"); + +clear WITHOUT_AUTO_PUTLHSVAR toolbox_title Function_Names Files Linker_Flag C_Flags; diff --git a/sci_gateway/cpp/libFAMOS.so b/sci_gateway/cpp/libFAMOS.so index d3b1e35..4a210ee 100755 Binary files a/sci_gateway/cpp/libFAMOS.so and b/sci_gateway/cpp/libFAMOS.so differ diff --git a/sci_gateway/cpp/sci_iofunc.cpp b/sci_gateway/cpp/sci_iofunc.cpp index 8895010..e1c8610 100644 --- a/sci_gateway/cpp/sci_iofunc.cpp +++ b/sci_gateway/cpp/sci_iofunc.cpp @@ -173,7 +173,7 @@ int return0toScilab() //make it the output variable AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx)+1; //return it to scilab - ReturnArguments(pvApiCtx); + //ReturnArguments(pvApiCtx); return 0; } @@ -189,6 +189,6 @@ int returnDoubleToScilab(double retVal) return 1; } AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx)+1; - ReturnArguments(pvApiCtx); + //ReturnArguments(pvApiCtx); return 0; } diff --git a/sci_gateway/cpp/sci_ipopt.cpp b/sci_gateway/cpp/sci_ipopt.cpp index 5837df1..4168488 100644 --- a/sci_gateway/cpp/sci_ipopt.cpp +++ b/sci_gateway/cpp/sci_ipopt.cpp @@ -4,6 +4,7 @@ Sai Kiran Keyur Joshi Iswarya + Harpreet Singh */ @@ -51,13 +52,14 @@ bool readSparse(int arg,int *iRows,int *iCols,int *iNbItem,int** piNbItemRow, in int sci_solveqp(char *fname) { - CheckInputArgument(pvApiCtx, 10, 10); // We need total 10 input arguments. + CheckInputArgument(pvApiCtx, 11, 11); // We need total 10 input arguments. CheckOutputArgument(pvApiCtx, 7, 7); // Error management variable SciErr sciErr; - int retVal=0, *piAddressVarQ = NULL,*piAddressVarP = NULL,*piAddressVarCM = NULL,*piAddressVarCUB = NULL,*piAddressVarCLB = NULL, *piAddressVarLB = NULL,*piAddressVarUB = NULL,*piAddressVarG = NULL; - double *QItems=NULL,*PItems=NULL,*ConItems=NULL,*conUB=NULL,*conLB=NULL,*varUB=NULL,*varLB=NULL,*init_guess = NULL,x,f,iter; + int retVal=0, *piAddressVarQ = NULL,*piAddressVarP = NULL,*piAddressVarCM = NULL,*piAddressVarCUB = NULL,*piAddressVarCLB = NULL, *piAddressVarLB = NULL,*piAddressVarUB = NULL,*piAddressVarG = NULL,*piAddressVarParam = NULL; + double *QItems=NULL,*PItems=NULL,*ConItems=NULL,*conUB=NULL,*conLB=NULL,*varUB=NULL,*varLB=NULL,*init_guess = NULL; + double *cpu_time=NULL, *max_iter=NULL, x,f,iter; static unsigned int nVars = 0,nCons = 0; unsigned int temp1 = 0,temp2 = 0; @@ -294,6 +296,34 @@ int sci_solveqp(char *fname) return 0; } + //Setting the parameters + /* get Address of inputs */ + sciErr = getVarAddressFromPosition(pvApiCtx, 11, &piAddressVarParam); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + temp1 = 1; + temp2 = 1; + + /* get matrix */ + sciErr = getMatrixOfDoubleInList(pvApiCtx, piAddressVarParam, 2, &temp1,&temp2, &max_iter); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + /* get matrix */ + sciErr = getMatrixOfDoubleInList(pvApiCtx, piAddressVarParam, 4, &temp1,&temp2, &cpu_time); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + using namespace Ipopt; SmartPtr Prob = new QuadNLP(nVars,nCons,QItems,PItems,ConItems,conUB,conLB,varUB,varLB,init_guess); @@ -304,6 +334,8 @@ int sci_solveqp(char *fname) // Note: The following choices are only examples, they might not be // suitable for your optimization problem. app->Options()->SetNumericValue("tol", 1e-7); + app->Options()->SetIntegerValue("max_iter", (int)*max_iter); + app->Options()->SetNumericValue("max_cpu_time", *cpu_time); app->Options()->SetStringValue("mu_strategy", "adaptive"); // Indicates whether all equality constraints are linear diff --git a/sci_gateway/cpp/sci_sym_getrowact.cpp b/sci_gateway/cpp/sci_sym_getrowact.cpp index fac3ddf..ebfd9ff 100644 --- a/sci_gateway/cpp/sci_sym_getrowact.cpp +++ b/sci_gateway/cpp/sci_sym_getrowact.cpp @@ -58,7 +58,7 @@ int sci_sym_getRowActivity(char *fname){ return 1; } AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx)+1; - ReturnArguments(pvApiCtx); + //ReturnArguments(pvApiCtx); delete[] rowAct; diff --git a/sci_gateway/cpp/sci_sym_loadproblem.cpp b/sci_gateway/cpp/sci_sym_loadproblem.cpp index 6d7f538..b732eeb 100644 --- a/sci_gateway/cpp/sci_sym_loadproblem.cpp +++ b/sci_gateway/cpp/sci_sym_loadproblem.cpp @@ -42,7 +42,7 @@ static void cleanupBeforeExit() return; } AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx)+1; - ReturnArguments(pvApiCtx); + //ReturnArguments(pvApiCtx); } static int checkNumArgs() diff --git a/sci_gateway/cpp/sci_sym_remove.cpp b/sci_gateway/cpp/sci_sym_remove.cpp index d4e9c49..be9c72b 100644 --- a/sci_gateway/cpp/sci_sym_remove.cpp +++ b/sci_gateway/cpp/sci_sym_remove.cpp @@ -126,7 +126,7 @@ int sci_sym_delete_cols(char *fname, unsigned long fname_len){ } AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; - ReturnArguments(pvApiCtx); + //ReturnArguments(pvApiCtx); free(value);//freeing the memory of the allocated pointer return 0; } @@ -242,7 +242,7 @@ int sci_sym_delete_rows(char *fname, unsigned long fname_len){ } AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; - ReturnArguments(pvApiCtx); + //ReturnArguments(pvApiCtx); free(value);//freeing the memory of the allocated pointer return 0; } diff --git a/sci_gateway/cpp/sci_sym_set_variables.cpp b/sci_gateway/cpp/sci_sym_set_variables.cpp index 327bf84..384de6f 100644 --- a/sci_gateway/cpp/sci_sym_set_variables.cpp +++ b/sci_gateway/cpp/sci_sym_set_variables.cpp @@ -50,7 +50,7 @@ int sci_sym_set_defaults(char *fname, unsigned long fname_len){ } AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; - ReturnArguments(pvApiCtx); + //ReturnArguments(pvApiCtx); return 0; } @@ -123,7 +123,7 @@ int sci_sym_set_int_param(char *fname, unsigned long fname_len){ } AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; - ReturnArguments(pvApiCtx); + //ReturnArguments(pvApiCtx); return 0; } @@ -181,7 +181,7 @@ int sci_sym_get_int_param(char *fname, unsigned long fname_len){ } AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; - ReturnArguments(pvApiCtx); + //ReturnArguments(pvApiCtx); return 0; } @@ -243,7 +243,7 @@ int sci_sym_set_dbl_param(char *fname, unsigned long fname_len){ } AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; - ReturnArguments(pvApiCtx); + //ReturnArguments(pvApiCtx); return 0; } @@ -302,7 +302,7 @@ int sci_sym_get_dbl_param(char *fname, unsigned long fname_len){ } AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; - ReturnArguments(pvApiCtx); + //ReturnArguments(pvApiCtx); return 0; } @@ -363,7 +363,7 @@ int sci_sym_set_str_param(char *fname, unsigned long fname_len){ } AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; - ReturnArguments(pvApiCtx); + //ReturnArguments(pvApiCtx); return 0; } @@ -421,7 +421,7 @@ int sci_sym_get_str_param(char *fname, unsigned long fname_len){ } AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; - ReturnArguments(pvApiCtx); + //ReturnArguments(pvApiCtx); return 0; } diff --git a/sci_gateway/cpp/sci_sym_solution.cpp b/sci_gateway/cpp/sci_sym_solution.cpp index a08e5b9..dff3b60 100644 --- a/sci_gateway/cpp/sci_sym_solution.cpp +++ b/sci_gateway/cpp/sci_sym_solution.cpp @@ -58,7 +58,7 @@ int sci_sym_getVarSoln(char *fname){ return 1; } AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx)+1; - ReturnArguments(pvApiCtx); + //ReturnArguments(pvApiCtx); delete[] solution; diff --git a/sci_gateway/cpp/sci_sym_solve.cpp~ b/sci_gateway/cpp/sci_sym_solve.cpp~ new file mode 100644 index 0000000..4abb268 --- /dev/null +++ b/sci_gateway/cpp/sci_sym_solve.cpp~ @@ -0,0 +1,49 @@ +/* + * Implementation Symphony Tool Box for Scilab + * Contains sym_solve function + * Author : Sai Kiran + */ + +#include +#include +extern sym_environment* global_sym_env;//defined in globals.cpp + +extern "C" { +#include +#include +#include +#include +#include +#include +int process_ret_val(int); + +int sci_sym_solve(char *fname, unsigned long fname_len){ + + int status=0; + + //check whether we have no input and one output argument or not + CheckInputArgument(pvApiCtx, 0, 0) ;//no input argument + CheckOutputArgument(pvApiCtx, 1, 1) ;//one output argument + + // Check environment + if(global_sym_env==NULL) + sciprint("Error: Symphony environment is not initialized.\n"); + else {// There is an environment opened + double time_limit = -1.0; + status = sym_get_dbl_param(global_sym_env,"time_limit",&time_limit); + + if (status == FUNCTION_TERMINATED_NORMALLY) { + if ( time_limit < 0.0 ) + sciprint("\nNote: There is no limit on time.\n"); + else sciprint("\nNote: Time limit has been set to %lf.\n",time_limit); + status=process_ret_val(sym_solve(global_sym_env));// Call function + } + else { + sciprint("\nUnable to read time limit.\n"); + status = 1; //Error state + } + } + // Return result to scilab + return returnDoubleToScilab(status); + } +} diff --git a/sci_gateway/cpp/sym_data_query_functions.cpp b/sci_gateway/cpp/sym_data_query_functions.cpp index b0d0989..9f38094 100644 --- a/sci_gateway/cpp/sym_data_query_functions.cpp +++ b/sci_gateway/cpp/sym_data_query_functions.cpp @@ -162,7 +162,7 @@ int sci_sym_get_dbl_arr(char *fname, unsigned long fname_len){ //assign result position to output argument AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; - ReturnArguments(pvApiCtx); + //ReturnArguments(pvApiCtx); return 0; } @@ -230,7 +230,7 @@ int sci_sym_get_row_sense(char *fname, unsigned long fname_len) { //assign result position to output argument AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; - ReturnArguments(pvApiCtx); + //ReturnArguments(pvApiCtx); return 0; } @@ -339,7 +339,7 @@ int sci_sym_get_matrix(char *fname, unsigned long fname_len){ //assign result position to output argument AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx) + 1; - ReturnArguments(pvApiCtx); + //ReturnArguments(pvApiCtx); return 0; } diff --git a/tests/unit_tests/README.rst b/tests/unit_tests/README.rst new file mode 100644 index 0000000..266e05c --- /dev/null +++ b/tests/unit_tests/README.rst @@ -0,0 +1,4 @@ +UNIT TESTS +========== + +These are test files for qpipopt, qpipoptmat, symphony and symphonymat. Generated by examples from demo files. diff --git a/tests/unit_tests/README.rst~ b/tests/unit_tests/README.rst~ new file mode 100644 index 0000000..e69de29 diff --git a/tests/unit_tests/qpipopt_base.dia.ref b/tests/unit_tests/qpipopt_base.dia.ref new file mode 100644 index 0000000..ffe546a --- /dev/null +++ b/tests/unit_tests/qpipopt_base.dia.ref @@ -0,0 +1,76 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// Author: Harpreet Singh +// Organization: FOSSEE, IIT Bombay +// Email: harpreet.mertia@gmail.com +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt + +// <-- JVM NOT MANDATORY --> +// <-- ENGLISH IMPOSED --> + + +// +// assert_close -- +// Returns 1 if the two real matrices computed and expected are close, +// i.e. if the relative distance between computed and expected is lesser than epsilon. +// Arguments +// computed, expected : the two matrices to compare +// epsilon : a small number +// +function flag = assert_close ( computed, expected, epsilon ) + if expected==0.0 then + shift = norm(computed-expected); + else + shift = norm(computed-expected)/norm(expected); + end +// if shift < epsilon then +// flag = 1; +// else +// flag = 0; +// end +// if flag <> 1 then pause,end + flag = assert_checktrue ( shift < epsilon ); +endfunction +// +// assert_equal -- +// Returns 1 if the two real matrices computed and expected are equal. +// Arguments +// computed, expected : the two matrices to compare +// epsilon : a small number +// +//function flag = assert_equal ( computed , expected ) +// if computed==expected then +// flag = 1; +// else +// flag = 0; +// end +// if flag <> 1 then pause,end +//endfunction + +//Find the value of x that minimize following function +// f(x) = 0.5*x1^2 + x2^2 - x1*x2 - 2*x1 - 6*x2 +// Subject to: +// x1 + x2 ≤ 2 +// –x1 + 2x2 ≤ 2 +// 2x1 + x2 ≤ 3 +// 0 ≤ x1, 0 ≤ x2. +Q = [1 -1; -1 2]; +p = [-2; -6]; +conMatrix = [1 1; -1 2; 2 1]; +conUB = [2; 2; 3]; +conLB = [-%inf; -%inf; -%inf]; +lb = [0; 0]; +ub = [%inf; %inf]; +nbVar = 2; +nbCon = 3; +[xopt,fopt,exitflag,output,lambda] = qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB) + +assert_close ( x , [0.6666667 1.3333333]' , 1.e-7 ); +assert_close ( f , [ - 8.2222223] , 1.e-7 ); + +assert_checkequal( exitflag , 0 ); diff --git a/tests/unit_tests/qpipopt_base.tst b/tests/unit_tests/qpipopt_base.tst new file mode 100644 index 0000000..ffe546a --- /dev/null +++ b/tests/unit_tests/qpipopt_base.tst @@ -0,0 +1,76 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// Author: Harpreet Singh +// Organization: FOSSEE, IIT Bombay +// Email: harpreet.mertia@gmail.com +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt + +// <-- JVM NOT MANDATORY --> +// <-- ENGLISH IMPOSED --> + + +// +// assert_close -- +// Returns 1 if the two real matrices computed and expected are close, +// i.e. if the relative distance between computed and expected is lesser than epsilon. +// Arguments +// computed, expected : the two matrices to compare +// epsilon : a small number +// +function flag = assert_close ( computed, expected, epsilon ) + if expected==0.0 then + shift = norm(computed-expected); + else + shift = norm(computed-expected)/norm(expected); + end +// if shift < epsilon then +// flag = 1; +// else +// flag = 0; +// end +// if flag <> 1 then pause,end + flag = assert_checktrue ( shift < epsilon ); +endfunction +// +// assert_equal -- +// Returns 1 if the two real matrices computed and expected are equal. +// Arguments +// computed, expected : the two matrices to compare +// epsilon : a small number +// +//function flag = assert_equal ( computed , expected ) +// if computed==expected then +// flag = 1; +// else +// flag = 0; +// end +// if flag <> 1 then pause,end +//endfunction + +//Find the value of x that minimize following function +// f(x) = 0.5*x1^2 + x2^2 - x1*x2 - 2*x1 - 6*x2 +// Subject to: +// x1 + x2 ≤ 2 +// –x1 + 2x2 ≤ 2 +// 2x1 + x2 ≤ 3 +// 0 ≤ x1, 0 ≤ x2. +Q = [1 -1; -1 2]; +p = [-2; -6]; +conMatrix = [1 1; -1 2; 2 1]; +conUB = [2; 2; 3]; +conLB = [-%inf; -%inf; -%inf]; +lb = [0; 0]; +ub = [%inf; %inf]; +nbVar = 2; +nbCon = 3; +[xopt,fopt,exitflag,output,lambda] = qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB) + +assert_close ( x , [0.6666667 1.3333333]' , 1.e-7 ); +assert_close ( f , [ - 8.2222223] , 1.e-7 ); + +assert_checkequal( exitflag , 0 ); diff --git a/tests/unit_tests/qpipopt_base.tst~ b/tests/unit_tests/qpipopt_base.tst~ new file mode 100644 index 0000000..9de0d6b --- /dev/null +++ b/tests/unit_tests/qpipopt_base.tst~ @@ -0,0 +1,76 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// Author: Harpreet Singh +// Organization: FOSSEE, IIT Bombay +// Email: harpreet.mertia@gmail.com +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt + +// <-- JVM NOT MANDATORY --> +// <-- ENGLISH IMPOSED --> + + +// +// assert_close -- +// Returns 1 if the two real matrices computed and expected are close, +// i.e. if the relative distance between computed and expected is lesser than epsilon. +// Arguments +// computed, expected : the two matrices to compare +// epsilon : a small number +// +function flag = assert_close ( computed, expected, epsilon ) + if expected==0.0 then + shift = norm(computed-expected); + else + shift = norm(computed-expected)/norm(expected); + end +// if shift < epsilon then +// flag = 1; +// else +// flag = 0; +// end +// if flag <> 1 then pause,end + flag = assert_checktrue ( shift < epsilon ); +endfunction +// +// assert_equal -- +// Returns 1 if the two real matrices computed and expected are equal. +// Arguments +// computed, expected : the two matrices to compare +// epsilon : a small number +// +//function flag = assert_equal ( computed , expected ) +// if computed==expected then +// flag = 1; +// else +// flag = 0; +// end +// if flag <> 1 then pause,end +//endfunction + +///Find the value of x that minimize following function +// f(x) = 0.5*x1^2 + x2^2 - x1*x2 - 2*x1 - 6*x2 +// Subject to: +// x1 + x2 ≤ 2 +// –x1 + 2x2 ≤ 2 +// 2x1 + x2 ≤ 3 +// 0 ≤ x1, 0 ≤ x2. +Q = [1 -1; -1 2]; +p = [-2; -6]; +conMatrix = [1 1; -1 2; 2 1]; +conUB = [2; 2; 3]; +conLB = [-%inf; -%inf; -%inf]; +lb = [0; 0]; +ub = [%inf; %inf]; +nbVar = 2; +nbCon = 3; +[xopt,fopt,exitflag,output,lambda] = qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB) + +assert_close ( x , [0.6666667 1.3333333]' , 1.e-7 ); +assert_close ( f , [ - 8.2222223] , 1.e-7 ); + +assert_checkequal( exitflag , 0 ); diff --git a/tests/unit_tests/qpipoptmat_base .dia.ref b/tests/unit_tests/qpipoptmat_base .dia.ref new file mode 100644 index 0000000..aacbc4e --- /dev/null +++ b/tests/unit_tests/qpipoptmat_base .dia.ref @@ -0,0 +1,73 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// Author: Harpreet Singh +// Organization: FOSSEE, IIT Bombay +// Email: harpreet.mertia@gmail.com +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt + +// <-- JVM NOT MANDATORY --> +// <-- ENGLISH IMPOSED --> + + +// +// assert_close -- +// Returns 1 if the two real matrices computed and expected are close, +// i.e. if the relative distance between computed and expected is lesser than epsilon. +// Arguments +// computed, expected : the two matrices to compare +// epsilon : a small number +// +function flag = assert_close ( computed, expected, epsilon ) + if expected==0.0 then + shift = norm(computed-expected); + else + shift = norm(computed-expected)/norm(expected); + end +// if shift < epsilon then +// flag = 1; +// else +// flag = 0; +// end +// if flag <> 1 then pause,end + flag = assert_checktrue ( shift < epsilon ); +endfunction +// +// assert_equal -- +// Returns 1 if the two real matrices computed and expected are equal. +// Arguments +// computed, expected : the two matrices to compare +// epsilon : a small number +// +//function flag = assert_equal ( computed , expected ) +// if computed==expected then +// flag = 1; +// else +// flag = 0; +// end +// if flag <> 1 then pause,end +//endfunction + +//Find the value of x that minimize following function +// f(x) = 0.5*x1^2 + x2^2 - x1*x2 - 2*x1 - 6*x2 +// Subject to: +// x1 + x2 ≤ 2 +// –x1 + 2x2 ≤ 2 +// 2x1 + x2 ≤ 3 +// 0 ≤ x1, 0 ≤ x2. +H = [1 -1; -1 2]; +f = [-2; -6]; +A = [1 1; -1 2; 2 1]; +b = [2; 2; 3]; +lb = [0; 0]; +ub = [%inf; %inf]; +[xopt,fopt,exitflag,output,lambda] = qpipoptmat(H,f,A,b,[],[],lb,ub) + +assert_close ( x , [0.6666667 1.3333333]' , 1.e-7 ); +assert_close ( f , [ - 8.2222223] , 1.e-7 ); + +assert_checkequal( exitflag , 0 ); diff --git a/tests/unit_tests/qpipoptmat_base .tst b/tests/unit_tests/qpipoptmat_base .tst new file mode 100644 index 0000000..aacbc4e --- /dev/null +++ b/tests/unit_tests/qpipoptmat_base .tst @@ -0,0 +1,73 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// Author: Harpreet Singh +// Organization: FOSSEE, IIT Bombay +// Email: harpreet.mertia@gmail.com +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt + +// <-- JVM NOT MANDATORY --> +// <-- ENGLISH IMPOSED --> + + +// +// assert_close -- +// Returns 1 if the two real matrices computed and expected are close, +// i.e. if the relative distance between computed and expected is lesser than epsilon. +// Arguments +// computed, expected : the two matrices to compare +// epsilon : a small number +// +function flag = assert_close ( computed, expected, epsilon ) + if expected==0.0 then + shift = norm(computed-expected); + else + shift = norm(computed-expected)/norm(expected); + end +// if shift < epsilon then +// flag = 1; +// else +// flag = 0; +// end +// if flag <> 1 then pause,end + flag = assert_checktrue ( shift < epsilon ); +endfunction +// +// assert_equal -- +// Returns 1 if the two real matrices computed and expected are equal. +// Arguments +// computed, expected : the two matrices to compare +// epsilon : a small number +// +//function flag = assert_equal ( computed , expected ) +// if computed==expected then +// flag = 1; +// else +// flag = 0; +// end +// if flag <> 1 then pause,end +//endfunction + +//Find the value of x that minimize following function +// f(x) = 0.5*x1^2 + x2^2 - x1*x2 - 2*x1 - 6*x2 +// Subject to: +// x1 + x2 ≤ 2 +// –x1 + 2x2 ≤ 2 +// 2x1 + x2 ≤ 3 +// 0 ≤ x1, 0 ≤ x2. +H = [1 -1; -1 2]; +f = [-2; -6]; +A = [1 1; -1 2; 2 1]; +b = [2; 2; 3]; +lb = [0; 0]; +ub = [%inf; %inf]; +[xopt,fopt,exitflag,output,lambda] = qpipoptmat(H,f,A,b,[],[],lb,ub) + +assert_close ( x , [0.6666667 1.3333333]' , 1.e-7 ); +assert_close ( f , [ - 8.2222223] , 1.e-7 ); + +assert_checkequal( exitflag , 0 ); diff --git a/tests/unit_tests/qpipoptmat_base .tst~ b/tests/unit_tests/qpipoptmat_base .tst~ new file mode 100644 index 0000000..9de0d6b --- /dev/null +++ b/tests/unit_tests/qpipoptmat_base .tst~ @@ -0,0 +1,76 @@ +// Copyright (C) 2015 - IIT Bombay - FOSSEE +// +// Author: Harpreet Singh +// Organization: FOSSEE, IIT Bombay +// Email: harpreet.mertia@gmail.com +// +// This file must be used under the terms of the CeCILL. +// This source file is licensed as described in the file COPYING, which +// you should have received as part of this distribution. The terms +// are also available at +// http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt + +// <-- JVM NOT MANDATORY --> +// <-- ENGLISH IMPOSED --> + + +// +// assert_close -- +// Returns 1 if the two real matrices computed and expected are close, +// i.e. if the relative distance between computed and expected is lesser than epsilon. +// Arguments +// computed, expected : the two matrices to compare +// epsilon : a small number +// +function flag = assert_close ( computed, expected, epsilon ) + if expected==0.0 then + shift = norm(computed-expected); + else + shift = norm(computed-expected)/norm(expected); + end +// if shift < epsilon then +// flag = 1; +// else +// flag = 0; +// end +// if flag <> 1 then pause,end + flag = assert_checktrue ( shift < epsilon ); +endfunction +// +// assert_equal -- +// Returns 1 if the two real matrices computed and expected are equal. +// Arguments +// computed, expected : the two matrices to compare +// epsilon : a small number +// +//function flag = assert_equal ( computed , expected ) +// if computed==expected then +// flag = 1; +// else +// flag = 0; +// end +// if flag <> 1 then pause,end +//endfunction + +///Find the value of x that minimize following function +// f(x) = 0.5*x1^2 + x2^2 - x1*x2 - 2*x1 - 6*x2 +// Subject to: +// x1 + x2 ≤ 2 +// –x1 + 2x2 ≤ 2 +// 2x1 + x2 ≤ 3 +// 0 ≤ x1, 0 ≤ x2. +Q = [1 -1; -1 2]; +p = [-2; -6]; +conMatrix = [1 1; -1 2; 2 1]; +conUB = [2; 2; 3]; +conLB = [-%inf; -%inf; -%inf]; +lb = [0; 0]; +ub = [%inf; %inf]; +nbVar = 2; +nbCon = 3; +[xopt,fopt,exitflag,output,lambda] = qpipopt(nbVar,nbCon,Q,p,lb,ub,conMatrix,conLB,conUB) + +assert_close ( x , [0.6666667 1.3333333]' , 1.e-7 ); +assert_close ( f , [ - 8.2222223] , 1.e-7 ); + +assert_checkequal( exitflag , 0 ); diff --git a/thirdparty/linux/README.rst b/thirdparty/linux/README.rst new file mode 100644 index 0000000..bddf213 --- /dev/null +++ b/thirdparty/linux/README.rst @@ -0,0 +1,4 @@ +THIRD PARTY LINUX +================= + +Third party C libraries of symphony and IPOpt. Installed in Ubuntu 64 and 32 bit. diff --git a/thirdparty/linux/README.rst~ b/thirdparty/linux/README.rst~ new file mode 100644 index 0000000..280ed22 --- /dev/null +++ b/thirdparty/linux/README.rst~ @@ -0,0 +1,4 @@ +THIRD PARTY LINUX +================= + + diff --git a/thirdparty/linux/lib/x86/libcoinblas.la b/thirdparty/linux/lib/x86/libcoinblas.la new file mode 100755 index 0000000..9386e57 --- /dev/null +++ b/thirdparty/linux/lib/x86/libcoinblas.la @@ -0,0 +1,35 @@ +# libcoinblas.la - a libtool library file +# Generated by ltmain.sh - GNU libtool 1.5.22 (1.1220.2.365 2005/12/18 22:14:06) +# +# Please DO NOT delete this file! +# It is necessary for linking the library. + +# The name that we can dlopen(3). +dlname='libcoinblas.so.1' + +# Names of this library. +library_names='libcoinblas.so.1.4.4 libcoinblas.so.1 libcoinblas.so' + +# The name of the static archive. +old_library='' + +# Libraries that this one depends upon. +dependency_libs='' + +# Version information for libcoinblas. +current=5 +age=4 +revision=4 + +# Is this an already installed library? +installed=yes + +# Should we warn about portability when linking against -modules? +shouldnotlink=no + +# Files to dlopen/dlpreopen +dlopen='' +dlpreopen='' + +# Directory that this library needs to be installed in: +libdir='/home/mushirahmed/Desktop/Ipopt-3.12.4/build32_ipopt/lib' diff --git a/thirdparty/linux/lib/x86/libcoinblas.so b/thirdparty/linux/lib/x86/libcoinblas.so new file mode 120000 index 0000000..ddd18ab --- /dev/null +++ b/thirdparty/linux/lib/x86/libcoinblas.so @@ -0,0 +1 @@ +libcoinblas.so.1.4.4 \ No newline at end of file diff --git a/thirdparty/linux/lib/x86/libcoinblas.so.1 b/thirdparty/linux/lib/x86/libcoinblas.so.1 new file mode 120000 index 0000000..ddd18ab --- /dev/null +++ b/thirdparty/linux/lib/x86/libcoinblas.so.1 @@ -0,0 +1 @@ +libcoinblas.so.1.4.4 \ No newline at end of file diff --git a/thirdparty/linux/lib/x86/libcoinblas.so.1.4.4 b/thirdparty/linux/lib/x86/libcoinblas.so.1.4.4 new file mode 100755 index 0000000..a1a56f6 Binary files /dev/null and b/thirdparty/linux/lib/x86/libcoinblas.so.1.4.4 differ diff --git a/thirdparty/linux/lib/x86/libcoinlapack.la b/thirdparty/linux/lib/x86/libcoinlapack.la new file mode 100755 index 0000000..8c9b979 --- /dev/null +++ b/thirdparty/linux/lib/x86/libcoinlapack.la @@ -0,0 +1,35 @@ +# libcoinlapack.la - a libtool library file +# Generated by ltmain.sh - GNU libtool 1.5.22 (1.1220.2.365 2005/12/18 22:14:06) +# +# Please DO NOT delete this file! +# It is necessary for linking the library. + +# The name that we can dlopen(3). +dlname='libcoinlapack.so.1' + +# Names of this library. +library_names='libcoinlapack.so.1.5.4 libcoinlapack.so.1 libcoinlapack.so' + +# The name of the static archive. +old_library='' + +# Libraries that this one depends upon. +dependency_libs=' -lblas' + +# Version information for libcoinlapack. +current=6 +age=5 +revision=4 + +# Is this an already installed library? +installed=yes + +# Should we warn about portability when linking against -modules? +shouldnotlink=no + +# Files to dlopen/dlpreopen +dlopen='' +dlpreopen='' + +# Directory that this library needs to be installed in: +libdir='/home/mushirahmed/Desktop/Ipopt-3.12.4/build32_ipopt/lib' diff --git a/thirdparty/linux/lib/x86/libcoinlapack.so b/thirdparty/linux/lib/x86/libcoinlapack.so new file mode 120000 index 0000000..68af160 --- /dev/null +++ b/thirdparty/linux/lib/x86/libcoinlapack.so @@ -0,0 +1 @@ +libcoinlapack.so.1.5.4 \ No newline at end of file diff --git a/thirdparty/linux/lib/x86/libcoinlapack.so.1 b/thirdparty/linux/lib/x86/libcoinlapack.so.1 new file mode 120000 index 0000000..68af160 --- /dev/null +++ b/thirdparty/linux/lib/x86/libcoinlapack.so.1 @@ -0,0 +1 @@ +libcoinlapack.so.1.5.4 \ No newline at end of file diff --git a/thirdparty/linux/lib/x86/libcoinlapack.so.1.5.4 b/thirdparty/linux/lib/x86/libcoinlapack.so.1.5.4 new file mode 100755 index 0000000..fd3453e Binary files /dev/null and b/thirdparty/linux/lib/x86/libcoinlapack.so.1.5.4 differ diff --git a/thirdparty/linux/lib/x86/libcoinmumps.la b/thirdparty/linux/lib/x86/libcoinmumps.la index 22e37ea..944fd37 100755 --- a/thirdparty/linux/lib/x86/libcoinmumps.la +++ b/thirdparty/linux/lib/x86/libcoinmumps.la @@ -8,18 +8,18 @@ dlname='libcoinmumps.so.1' # Names of this library. -library_names='libcoinmumps.so.1.4.7 libcoinmumps.so.1 libcoinmumps.so' +library_names='libcoinmumps.so.1.5.4 libcoinmumps.so.1 libcoinmumps.so' # The name of the static archive. old_library='' # Libraries that this one depends upon. -dependency_libs='' +dependency_libs=' -lblas -L/usr/lib/gcc/i686-linux-gnu/4.6 -L/usr/lib/gcc/i686-linux-gnu/4.6/../../../i386-linux-gnu -L/usr/lib/gcc/i686-linux-gnu/4.6/../../../../lib -L/lib/i386-linux-gnu -L/lib/../lib -L/usr/lib/i386-linux-gnu -L/usr/lib/../lib -L/usr/lib/gcc/i686-linux-gnu/4.6/../../.. -lgfortran -lm -lquadmath' # Version information for libcoinmumps. -current=5 -age=4 -revision=7 +current=6 +age=5 +revision=4 # Is this an already installed library? installed=yes @@ -32,4 +32,4 @@ dlopen='' dlpreopen='' # Directory that this library needs to be installed in: -libdir='/home/tonio/Ipopt-3.11.0/build/lib' +libdir='/home/mushirahmed/Desktop/Ipopt-3.12.4/build32_ipopt/lib' diff --git a/thirdparty/linux/lib/x86/libcoinmumps.so b/thirdparty/linux/lib/x86/libcoinmumps.so index 1a9edbe..c2d14a9 120000 --- a/thirdparty/linux/lib/x86/libcoinmumps.so +++ b/thirdparty/linux/lib/x86/libcoinmumps.so @@ -1 +1 @@ -libcoinmumps.so.1.4.7 \ No newline at end of file +libcoinmumps.so.1.5.4 \ No newline at end of file diff --git a/thirdparty/linux/lib/x86/libcoinmumps.so.1 b/thirdparty/linux/lib/x86/libcoinmumps.so.1 index 1a9edbe..c2d14a9 120000 --- a/thirdparty/linux/lib/x86/libcoinmumps.so.1 +++ b/thirdparty/linux/lib/x86/libcoinmumps.so.1 @@ -1 +1 @@ -libcoinmumps.so.1.4.7 \ No newline at end of file +libcoinmumps.so.1.5.4 \ No newline at end of file diff --git a/thirdparty/linux/lib/x86/libcoinmumps.so.1.5.4 b/thirdparty/linux/lib/x86/libcoinmumps.so.1.5.4 new file mode 100755 index 0000000..deeb8d3 Binary files /dev/null and b/thirdparty/linux/lib/x86/libcoinmumps.so.1.5.4 differ diff --git a/thirdparty/linux/lib/x86/libipopt.la b/thirdparty/linux/lib/x86/libipopt.la index d38333a..e7d4b76 100755 --- a/thirdparty/linux/lib/x86/libipopt.la +++ b/thirdparty/linux/lib/x86/libipopt.la @@ -8,18 +8,18 @@ dlname='libipopt.so.1' # Names of this library. -library_names='libipopt.so.1.9.0 libipopt.so.1 libipopt.so' +library_names='libipopt.so.1.10.4 libipopt.so.1 libipopt.so' # The name of the static archive. old_library='' # Libraries that this one depends upon. -dependency_libs='' +dependency_libs=' /home/mushirahmed/Desktop/Ipopt-3.12.4/build32_ipopt/lib/libcoinmumps.la -lgfortran -lquadmath -llapack -lblas -ldl' # Version information for libipopt. -current=10 -age=9 -revision=0 +current=11 +age=10 +revision=4 # Is this an already installed library? installed=yes @@ -32,4 +32,4 @@ dlopen='' dlpreopen='' # Directory that this library needs to be installed in: -libdir='/home/tonio/Ipopt-3.11.0/build/lib' +libdir='/home/mushirahmed/Desktop/Ipopt-3.12.4/build32_ipopt/lib' diff --git a/thirdparty/linux/lib/x86/libipopt.so b/thirdparty/linux/lib/x86/libipopt.so index eec8a79..5cfe046 120000 --- a/thirdparty/linux/lib/x86/libipopt.so +++ b/thirdparty/linux/lib/x86/libipopt.so @@ -1 +1 @@ -libipopt.so.1.9.0 \ No newline at end of file +libipopt.so.1.10.4 \ No newline at end of file diff --git a/thirdparty/linux/lib/x86/libipopt.so.1 b/thirdparty/linux/lib/x86/libipopt.so.1 index eec8a79..5cfe046 120000 --- a/thirdparty/linux/lib/x86/libipopt.so.1 +++ b/thirdparty/linux/lib/x86/libipopt.so.1 @@ -1 +1 @@ -libipopt.so.1.9.0 \ No newline at end of file +libipopt.so.1.10.4 \ No newline at end of file diff --git a/thirdparty/linux/lib/x86/libipopt.so.1.10.4 b/thirdparty/linux/lib/x86/libipopt.so.1.10.4 new file mode 100755 index 0000000..29c6300 Binary files /dev/null and b/thirdparty/linux/lib/x86/libipopt.so.1.10.4 differ -- cgit