/********************************************************
  Xpress-BCL C++ Example Problems
  ===============================

  file folioheur.cpp
  ``````````````````
  Modeling a small MIP problem
  to perform portfolio optimization.
   -- Heuristic solution --

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

#include <iostream>
#include "xprb_cpp.h"
#include "xprs.h"

using namespace std;
using namespace ::dashoptimization;

#define MAXNUM 4                   // Max. number of shares to be selected

#define NSHARES 10                 // Number of shares
#define NRISK 5                    // Number of high-risk shares
#define NNA 4                      // Number of North-American shares

void solveHeur(XPRBprob &p);

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

XPRBvar frac[NSHARES];             // Fraction of capital used per share
XPRBvar buy[NSHARES];              // 1 if asset is in portfolio, 0 otherwise

int main(int argc, char **argv)
{
 int s;
 XPRBexpr Risk,Na,Return,Cap,Num;

 XPRBprob p("FolioMIPHeur");       // Initialize a new problem in BCL

// Create the decision variables (including upper bounds for `frac')
 for(s=0;s<NSHARES;s++) frac[s]=p.newVar("frac", buy[s]=p.newVar("buy", Objective: total return for(s=0;s<NSHARES;s++) Return +=RET[s]*frac[s]; Set the objective function Limit percentage of high-risk values Risk <=1.0/3); Minimum amount North-American Na>= 0,5);

// Spend all the capital
 for(s=0;s<NSHARES;s++) Cap +=frac[s]; p.newCtr(Cap== Limit the total number of assets for(s=0;s<NSHARES;s++) Num <=MAXNUM); Linking variables Solve problem heuristically Solution printing if(p.getMIPStat()==XPRB_MIP_SOLUTION p.getMIPStat()==XPRB_MIP_OPTIMAL) cout <<="Exact solution: Total return: " s else return void XPRBbasis int double Disable automatic cuts Switch presolve off Get feasibility tolerance LP-relaxation basis=p.saveBasis(); Save current Fix all for which is at or a relatively large value fsol[s]=frac[s].getSol(); solution values> 0,2-TOL)  buy[s].setLB(1);
 }

 p.mipOptimize("c");               // Solve the MIP-problem
 ifgsol=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
  cout << "Heuristic solution: Total return: " << p.getObjVal() << endl;
  for(s=0;s<NSHARES;s++) cout s <<=": " Re-initialize the MIP search 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.reset();             // No need to store the saved basis any longer
 if(ifgsol==1)
  XPRSsetdblcontrol(p.getXPRSprob(), XPRS_MIPABSCUTOFF, solval+TOL);
                            // Set the cutoff to the best known solution

}