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-// 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,iter] = 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,iter] = 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
-  //   iter : a 1x1 matrix of doubles, contains the number od iterations done by symphony
-  //   
-  //   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 
-  //
-  //   <latex>
-  //    \begin{eqnarray}
-  //    &\mbox{min}_{x}
-  //    & f(x) \\
-  //    & \text{subject to} & conLB \geq C(x) \leq conUB \\
-  //    & & lb \geq x \leq ub \\
-  //    \end{eqnarray}
-  //   </latex>
-  //   
-  //   
-  //
-  //   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,iter] = 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,iter]= 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 = [];
-   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,iter] = symphony_call(nbVar,nbCon,objCoef,isInt,LB,UB,conMatrix,conLB,conUB,objSense,options);
-
-endfunction
-