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+<?xml version="1.0" encoding="UTF-8"?>
+
+<!--
+ *
+ * This help file was generated from symphony.sci using help_from_sci().
+ *
+ -->
+
+<refentry version="5.0-subset Scilab" xml:id="symphony" xml:lang="en"
+ xmlns="http://docbook.org/ns/docbook"
+ xmlns:xlink="http://www.w3.org/1999/xlink"
+ xmlns:svg="http://www.w3.org/2000/svg"
+ xmlns:ns3="http://www.w3.org/1999/xhtml"
+ xmlns:mml="http://www.w3.org/1998/Math/MathML"
+ xmlns:scilab="http://www.scilab.org"
+ xmlns:db="http://docbook.org/ns/docbook">
+
+ <refnamediv>
+ <refname>symphony</refname>
+ <refpurpose>Solves a mixed integer linear programming constrained optimization problem.</refpurpose>
+ </refnamediv>
+
+
+<refsynopsisdiv>
+ <title>Calling Sequence</title>
+ <synopsis>
+ 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( ... )
+
+ </synopsis>
+</refsynopsisdiv>
+
+<refsection>
+ <title>Parameters</title>
+ <variablelist>
+ <varlistentry><term>nbVar :</term>
+ <listitem><para> a 1 x 1 matrix of doubles, number of variables</para></listitem></varlistentry>
+ <varlistentry><term>nbCon :</term>
+ <listitem><para> a 1 x 1 matrix of doubles, number of constraints</para></listitem></varlistentry>
+ <varlistentry><term>objCoeff :</term>
+ <listitem><para> a 1 x n matrix of doubles, where n is number of variables, contains coefficients of the variables in the objective</para></listitem></varlistentry>
+ <varlistentry><term>isInt :</term>
+ <listitem><para> a 1 x n matrix of boolean, where n is number of variables, representing wether a variable is constrained to be an integer</para></listitem></varlistentry>
+ <varlistentry><term>LB :</term>
+ <listitem><para> a 1 x n matrix of doubles, where n is number of variables, contains lower bounds of the variables. Bound can be negative infinity</para></listitem></varlistentry>
+ <varlistentry><term>UB :</term>
+ <listitem><para> a 1 x n matrix of doubles, where n is number of variables, contains upper bounds of the variables. Bound can be infinity</para></listitem></varlistentry>
+ <varlistentry><term>conMatrix :</term>
+ <listitem><para> 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</para></listitem></varlistentry>
+ <varlistentry><term>conLB :</term>
+ <listitem><para> a m x 1 matrix of doubles, where m is number of constraints, contains lower bounds of the constraints.</para></listitem></varlistentry>
+ <varlistentry><term>conUB :</term>
+ <listitem><para> a m x 1 matrix of doubles, where m is number of constraints, contains upper bounds of the constraints</para></listitem></varlistentry>
+ <varlistentry><term>objSense :</term>
+ <listitem><para> The sense (maximization/minimization) of the objective. Use 1(sym_minimize ) or -1 (sym_maximize) here</para></listitem></varlistentry>
+ <varlistentry><term>options :</term>
+ <listitem><para> a 1xq marix of string, provided to set the paramters in symphony</para></listitem></varlistentry>
+ <varlistentry><term>xopt :</term>
+ <listitem><para> a 1xn matrix of doubles, the computed solution of the optimization problem</para></listitem></varlistentry>
+ <varlistentry><term>fopt :</term>
+ <listitem><para> a 1x1 matrix of doubles, the function value at x</para></listitem></varlistentry>
+ <varlistentry><term>iter :</term>
+ <listitem><para> a 1x1 matrix of doubles, contains the number od iterations done by symphony</para></listitem></varlistentry>
+ </variablelist>
+</refsection>
+
+<refsection>
+ <title>Description</title>
+ <para>
+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
+ </para>
+ <para>
+<latex>
+\begin{eqnarray}
+&amp;\mbox{min}_{x}
+&amp; f(x) \\
+&amp; \text{subject to} &amp; conLB \geq C(x) \leq conUB \\
+&amp; &amp; lb \geq x \leq ub \\
+\end{eqnarray}
+</latex>
+ </para>
+ <para>
+ </para>
+ <para>
+ </para>
+ <para>
+</para>
+</refsection>
+
+<refsection>
+ <title>Examples</title>
+ <programlisting role="example"><![CDATA[
+//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);
+ ]]></programlisting>
+</refsection>
+
+<refsection>
+ <title>Examples</title>
+ <programlisting role="example"><![CDATA[
+// 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)
+
+ ]]></programlisting>
+</refsection>
+
+<refsection>
+ <title>Authors</title>
+ <simplelist type="vert">
+ <member>Keyur Joshi, Saikiran, Iswarya, Harpreet Singh</member>
+ </simplelist>
+</refsection>
+</refentry>