// Copyright (C) 2016 - IIT Bombay - FOSSEE // // 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 // Author: Pranav Deshpande and Akshay Miterani // Organization: FOSSEE, IIT Bombay // Email: toolbox@scilab.in function [xopt,fopt,exitflag,output] = cbcintlinprog (varargin) // Solves a mixed integer linear programming constrained optimization problem in intlinprog format. // // Calling Sequence // xopt = cbcintlinprog(c,intcon,A,b) // xopt = cbcintlinprog(c,intcon,A,b,Aeq,beq) // xopt = cbcintlinprog(c,intcon,A,b,Aeq,beq,lb,ub) // xopt = cbcintlinprog(c,intcon,A,b,Aeq,beq,lb,ub,options) // xopt = cbcintlinprog('path_to_mps_file') // xopt = cbcintlinprog('path_to_mps_file',options) // [xopt,fopt,status,output] = cbcintlinprog( ... ) // // Parameters // 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 : a matrix of double, represents the linear coefficients in the inequality constraints A⋅x ≤ b. // b : a vector of double, represents the linear coefficients in the inequality constraints A⋅x ≤ b. // Aeq : a matrix of double, represents the linear coefficients in the equality constraints Aeq⋅x = beq. // beq : a vector of double, represents the linear coefficients in the equality constraints Aeq⋅x = beq. // 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 parameters to be set. // xopt : a vector of double, the computed solution of the optimization problem. // fopt : a double, the value of the function at x. // status : status flag returned from symphony. See below for details. // output : The output data structure contains detailed information about the optimization process. See below for details. // // Description // Search the minimum or maximum of a constrained mixed integer linear programming optimization problem specified by : // // // \begin{eqnarray} // &\mbox{min}_{x} // & 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 \!\, intcon\\ // \end{eqnarray} // // // Examples // // Objective function // // Reference: Westerberg, Carl-Henrik, Bengt Bjorklund, and Eskil Hultman. "An application of mixed integer programming in a Swedish steel mill." Interfaces 7, no. 2 (1977): 39-43. // 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] = cbcintlinprog(c,intcon,[],[],Aeq,beq,lb,ub) // // Press ENTER to continue // // 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) // 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 .. // 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 // 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; // //Constraint 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(c,1); // b=[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('MaxTime', 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 cbc // [x,f,status,output] = cbcintlinprog(c,intcon,A,b,[],[],lb,ub,options); // Authors // Akshay Miterani and Pranav Deshpande if(type(varargin(1))==1) then //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]"), "cbcintlinprog", rhs); error(errmsg); end c = []; intcon = []; A = []; b = []; Aeq = []; beq = []; lb = []; ub = []; options = list(); c = varargin(1) intcon = varargin(2) A = varargin(3) b = varargin(4) if(size(c,2) == 0) then errmsg = msprintf(gettext("%s: Cannot determine the number of variables because input objective coefficients is empty"),"cbcintlinprog"); error(errmsg); end if (size(c,2)~=1) then errmsg = msprintf(gettext("%s: Objective Coefficients should be a column matrix"), "cbcintlinprog"); error(errmsg); end nbVar = size(c,1); if ( rhs<5 ) then Aeq = [] beq = [] else Aeq = varargin(5); beq = varargin(6); end if ( rhs<7 ) then lb = repmat(-%inf,1,nbVar); ub = repmat(%inf,1,nbVar); else lb = varargin(7); ub = varargin(8); end if (rhs<9|size(varargin(9))==0) then options = list(); else options = varargin(9); end [xopt,fopt,exitflag,output]=cbcmatrixintlinprog(c,intcon,A,b,Aeq,beq,lb,ub,options); elseif(type(varargin(1))==10) then [lhs , rhs] = argn(); //To check the number of argument given by user if ( rhs < 1 | rhs > 2) then errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be in the set of [1 2]"),"cbcintlinprog",rhs); error(errmsg) end mpsFile = varargin(1); if ( rhs<2 | size(varargin(2)) ==0 ) then param = list(); else param =varargin(2); end [xopt,fopt,exitflag,output]=cbcmpsintlinprog(mpsFile,param); end endfunction