/********************************************************
  Xpress-BCL Java Example Problems
  ================================

  file folioheur.java
  ```````````````````
  Modeling a small LP problem 
  to perform portfolio optimization.
   -- Heuristic solution --

  (c) 2008 Fair Isaac Corporation
      author: S.Heipcke, 2003, rev. Dec. 2011
********************************************************/

import com.dashoptimization.*;

public class folioheur
{
 static final int MAXNUM = 4;      /* Max. number of different assets */
 static final int NSHARES = 10;    /* Number of shares */
 static final int NRISK = 5;       /* Number of high-risk shares */
 static final int NNA = 4;         /* Number of North-American shares */

 static final double[] RET = {5,17,26,12,8,9,7,6,31,21};
                                   /* Estimated return in investment  */
 static final int[] RISK = {1,2,3,8,9};  /* High-risk values among shares */
 static final int[] NA = {0,1,2,3};      /* Shares issued in N.-America */

 static XPRB bcl;
 static XPRBprob p;
 static XPRBvar[] frac;            /* Fraction of capital used per share */
 static XPRBvar[] buy;             /* 1 if asset is in portfolio, 0 otherwise */
 
 public static void main(String[] args) throws XPRSprobException, XPRSexception
 { 
  int s;
  XPRBexpr Risk,Na,Return,Cap,Num;

  bcl = new XPRB();                  /* Initialize BCL */
  XPRS.init();                       /* Initialize Xpress-Optimizer */
  p = bcl.newProb("FolioMIPHeur");   /* Create a new problem in BCL */

/* Create the decision variables */
  frac = new XPRBvar[NSHARES];
  buy = new XPRBvar[NSHARES];
  for(s=0;s<NSHARES;s++) frac[s]=p.newVar("frac", buy[s]=p.newVar("buy", Objective: total return Return=new for(s=0;s<NSHARES;s++) Set the objective function Limit percentage of high-risk values Risk=new Minimum amount North-American Na=new Spend all capital Cap=new number assets Num=new Linking variables Solve problem heuristically Solution printing if(p.getMIPStat()==XPRB.MIP_SOLUTION p.getMIPStat()==XPRB.MIP_OPTIMAL) solution: Total return:=" + p.getObjVal());
   for(s=0;s<NSHARES;s++) 
    System.out.println(s + " :=" + frac[s].getSol()*100 + " else solution is Delete p=null; static void throws XPRSprobException XPRSprob XPRBbasis int double op=p.getXPRSprob(); Retrieve Optimizer Disable automatic cuts Switch presolve off TOL=op.getDblControl(XPRS.FEASTOL); Get feasibility tolerance LP-problem basis=p.saveBasis(); Save current Fix for which at or a relatively large value fsol=new fsol[s]=frac[s].getSol();> 0,2-TOL)  buy[s].setLB(1);
  }

  p.mipOptimize("c");              /* Continue solving the MIP-problem */
  ifgsol=0; solval=0;
  if(p.getMIPStat()==XPRB.MIP_SOLUTION || p.getMIPStat()==XPRB.MIP_OPTIMAL)
  {                                /* If an integer feas. solution was found */
   ifgsol=1;
   solval=p.getObjVal();           /* Get the value of the best solution */
   System.out.println("Heuristic solution: Total return: " + p.getObjVal());
   for(s=0;s<NSHARES;s++) +=": " Reset variables to their original bounds for(s=0;s<NSHARES;s++)> 0,2-TOL))
   {
    buy[s].setLB(0);
    buy[s].setUB(1);
   }

  p.loadBasis(basis);       /* Load the saved basis: bound changes are
                               immediately passed on from BCL to the
                               Optimizer if the problem has not been modified
                               in any other way, so that there is no need to 
                               reload the matrix */
  basis = null;             /* No need to store the saved basis any longer */
  if(ifgsol==1)
   op.setDblControl(XPRS.MIPABSCUTOFF, solval+TOL);
                            /* Set the cutoff to the best known solution */
 } 
}