Help and Symphony equivalent to intlinprog

2 files changed, 89 insertions, 1 deletions

diff --git a/demos/symphony_knapsack.sce b/demos/symphony_knapsack.sce
index 854bf06..c6e5a51 100644
--- a/demos/symphony_knapsack.sce
+++ b/demos/symphony_knapsack.sce
@@ -95,7 +95,7 @@ conLB=repmat(0,nbCon,1);
 // Upper Bound of constraints
 conUB=[11927 13727 11551 13056 13460 ]';
 
-options = ["time_limit" "10"]
+options = ["time_limit" "25"]
 
 // The expected solution :
 
diff --git a/demos/symphony_mat_knapsack.sce b/demos/symphony_mat_knapsack.sce
new file mode 100644
index 0000000..76fefee
--- /dev/null
+++ b/demos/symphony_mat_knapsack.sce
@@ -0,0 +1,88 @@
+mode (-1)
+
+clc
+
+// Reference
+// 
+// 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
+// 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_mat(objCoef,intcon,conMatrix,conUB,[],[],lb,ub);
+