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Diffstat (limited to 'macros/symphonymat.sci')
| -rw-r--r-- | macros/symphonymat.sci | 215 |
1 files changed, 112 insertions, 103 deletions
diff --git a/macros/symphonymat.sci b/macros/symphonymat.sci index 9226bd6..2c0c18d 100644 --- a/macros/symphonymat.sci +++ b/macros/symphonymat.sci @@ -13,47 +13,47 @@ function [xopt,fopt,status,iter] = symphonymat (varargin) // Solves a mixed integer linear programming constrained optimization problem in intlinprog format. // // Calling Sequence - // xopt = symphonymat(C,intcon,A,b) - // xopt = symphonymat(C,intcon,A,b,Aeq,beq) - // xopt = symphonymat(C,intcon,A,b,Aeq,beq,lb,ub) - // xopt = symphonymat(C,intcon,A,b,Aeq,beq,lb,ub,options) + // xopt = symphonymat(c,intcon,A,b) + // xopt = symphonymat(c,intcon,A,b,Aeq,beq) + // xopt = symphonymat(c,intcon,A,b,Aeq,beq,lb,ub) + // xopt = symphonymat(c,intcon,A,b,Aeq,beq,lb,ub,options) // [xopt,fopt,status,output] = symphonymat( ... ) // // Parameters - // f : a vector of double, contains coefficients of the variables in the objective + // c : a vector of double, 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 double. 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 double. 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 double. 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 double. beq represents the constant vector in the constraints Aeq*x = beq. beq has length Meq, where Aeq is Meq-by-N. + // A : Linear inequality constraint matrix, specified as a matrix of double. A represents the linear coefficients in the constraints A*x ≤ b. A has the size where columns equals to the number of variables. + // b : Linear inequality constraint vector, specified as a vector of double. b represents the constant vector in the constraints A*x ≤ b. b has size equals to the number of rows in A. + // Aeq : Linear equality constraint matrix, specified as a matrix of double. Aeq represents the linear coefficients in the constraints Aeq*x = beq. Aeq has the size where columns equals to the number of variables. + // beq : Linear equality constraint vector, specified as a vector of double. beq represents the constant vector in the constraints Aeq*x = beq. beq has size equals to the number of rows in Aeq. // lb : Lower bounds, specified as a vector or array of double. lb represents the lower bounds elementwise in lb ≤ x ≤ ub. // ub : Upper bounds, specified as a vector or array of double. ub represents the upper bounds elementwise in lb ≤ x ≤ ub. // options : a list containing the the parameters to be set. - // xopt : a vector of double, the computed solution of the optimization problem + // xopt : a vector of double, the computed solution of the optimization problem. // fopt : a double, the function value at x - // status : status flag from symphony. - // output : The output data structure contains detailed informations about the optimization process. Right now it contains number of iteration. + // status : status flag from symphony. 227 is optimal, 228 is Time limit exceeded, 230 is iteration limit exceeded. + // output : The output data structure contains detailed information about the optimization process. This version only contains number of iterations. // // 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 + // find the minimum or maximum of C'⋅x such that // // <latex> // \begin{eqnarray} // &\mbox{min}_{x} - // & C^T*x \\ - // & \text{subject to} & A*x \leq b \\ - // & & Aeq*x = beq \\ + // & C^T⋅x \\ + // & \text{subject to} & A⋅x \leq b \\ + // & & Aeq⋅x = beq \\ // & & lb \leq x \leq ub \\ // & & x_i \in \!\, \mathbb{Z}, i \in \!\, I // \end{eqnarray} // </latex> // - // We are calling SYMPHONY written in C by gateway files for the actual computation. + // The routine calls SYMPHONY written in C by gateway files for the actual computation. // // Examples // // Objective function - // C = [350*5,330*3,310*4,280*6,500,450,400,100]'; + // 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 @@ -79,7 +79,7 @@ function [xopt,fopt,status,iter] = symphonymat (varargin) // // 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) - // C = -1*[ 504 803 667 1103 834 585 811 856 690 832 846 813 868 793 .. + // c = -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 .. @@ -88,47 +88,47 @@ function [xopt,fopt,status,iter] = symphonymat (varargin) // 1162 653 814 625 599 476 767 954 906 904 649 873 565 853 1008 632]'; // //Constraint Matrix // A = [ //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 ; + // 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,1) + // nbVar = size(c,1) // b=[11927 13727 11551 13056 13460 ]; // // Lower Bound of variables // lb = repmat(0,1,nbVar) @@ -148,7 +148,7 @@ function [xopt,fopt,status,iter] = symphonymat (varargin) // // Optimal value // fopt = [ 24381 ] // // Calling Symphony - // [x,f,status,output] = symphonymat(C,intcon,A,b,[],[],lb,ub,options); + // [x,f,status,output] = symphonymat(c,intcon,A,b,[],[],lb,ub,options); // Authors // Keyur Joshi, Saikiran, Iswarya, Harpreet Singh @@ -157,24 +157,33 @@ function [xopt,fopt,status,iter] = symphonymat (varargin) [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 - + 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) + c = []; + intcon = []; + A = []; + b = []; + Aeq = []; + beq = []; + lb = []; + ub = []; + + + c = varargin(1) + intcon = varargin(2) + A = varargin(3) + b = varargin(4) - if (size(objCoef,2)~=1) then + if (size(c,2)~=1) then errmsg = msprintf(gettext("%s: Objective Coefficients should be a column matrix"), "Symphonymat"); error(errmsg); end - nbVar = size(objCoef,1); + nbVar = size(c,1); if ( rhs<5 ) then Aeq = [] @@ -218,25 +227,25 @@ function [xopt,fopt,status,iter] = symphonymat (varargin) // Check if the user gives row vector // and Changing it to a column matrix - if (size(lb,2)== [nbVar]) then - lb = lb'; - end + if (size(lb,2)== [nbVar]) then + lb = lb'; + end - if (size(ub,2)== [nbVar]) then - ub = ub'; - end + if (size(ub,2)== [nbVar]) then + ub = ub'; + end - if (size(b,2)== [nbConInEq]) then - b = b'; - end + if (size(b,2)== [nbConInEq]) then + b = b'; + end - if (size(beq,2)== [nbConEq]) then - beq = beq'; - end + if (size(beq,2)== [nbConEq]) then + beq = beq'; + end for i=1:size(intcon,2) if(intcon(i)>nbVar) then - errmsg = msprintf(gettext("%s: The values inside intcon should not exceed total number of variable "), "Symphonymat"); + errmsg = msprintf(gettext("%s: The values inside intcon should be less than the number of variables"), "Symphonymat"); error(errmsg); end @@ -246,35 +255,35 @@ function [xopt,fopt,status,iter] = symphonymat (varargin) end if(modulo(intcon(i),1)) then - errmsg = msprintf(gettext("%s: The values inside intcon should be integer "), "Symphonymat"); + errmsg = msprintf(gettext("%s: The values inside intcon should be an integer "), "Symphonymat"); error(errmsg); end end //Check the size of inequality constraint which should equal to the number of inequality constraints - if ( size(A,2) ~= nbVar & size(A,2) ~= 0) then - errmsg = msprintf(gettext("%s: The size of inequality constraint is not equal to the number of variables"), "Symphonymat"); - error(errmsg); - end + if ( size(A,2) ~= nbVar & size(A,2) ~= 0) then + errmsg = msprintf(gettext("%s: The size of inequality constraint is not equal to the number of variables"), "Symphonymat"); + error(errmsg); + end //Check the size of lower bound of inequality constraint which should equal to the number of constraints - if ( size(b,1) ~= size(A,1)) then - errmsg = msprintf(gettext("%s: The Lower Bound of inequality constraint is not equal to the number of constraint"), "Symphonymat"); - error(errmsg); - end + if ( size(b,1) ~= size(A,1)) then + errmsg = msprintf(gettext("%s: The Lower Bound of inequality constraint is not equal to the number of constraint"), "Symphonymat"); + error(errmsg); + end //Check the size of equality constraint which should equal to the number of inequality constraints - if ( size(Aeq,2) ~= nbVar & size(Aeq,2) ~= 0) then - errmsg = msprintf(gettext("%s: The size of equality constraint is not equal to the number of variables"), "Symphonymat"); - error(errmsg); - end + if ( size(Aeq,2) ~= nbVar & size(Aeq,2) ~= 0) then + errmsg = msprintf(gettext("%s: The size of equality constraint is not equal to the number of variables"), "Symphonymat"); + error(errmsg); + end //Check the size of upper bound of equality constraint which should equal to the number of constraints - if ( size(beq,1) ~= size(Aeq,1)) then - errmsg = msprintf(gettext("%s: The equality constraint upper bound is not equal to the number of equality constraint"), "Symphonymat"); - error(errmsg); - end + if ( size(beq,1) ~= size(Aeq,1)) then + errmsg = msprintf(gettext("%s: The equality constraint upper bound is not equal to the number of equality constraint"), "Symphonymat"); + error(errmsg); + end //Check the size of Lower Bound which should equal to the number of variables if ( size(lb,1) ~= nbVar) then @@ -349,9 +358,9 @@ function [xopt,fopt,status,iter] = symphonymat (varargin) //Changing into row vector lb = lb'; ub = ub'; - objCoef = objCoef'; + c = c'; - [xopt,fopt,status,iter] = symphony_call(nbVar,nbCon,objCoef,isInt,lb,ub,conMatrix,conLB,conUB,objSense,options); + [xopt,fopt,status,iter] = symphony_call(nbVar,nbCon,c,isInt,lb,ub,conMatrix,conLB,conUB,objSense,options); endfunction |