Added macros for int and ecos functions

1 files changed, 234 insertions, 0 deletions

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+// 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 :
+    //
+    //   <latex>
+    //	\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}
+    //   </latex>
+    //
+	// 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