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

  file foliomip3.cpp
  ``````````````````
  Modeling a MIP problem
  to perform portfolio optimization.
   -- Extending the problem with constraints on
      the geographical and sectorial distributions --
   -- Working with a larger data set --

  (c) 2009-2024 Fair Isaac Corporation
      author: S.Heipcke, May 2009, rev. Mar. 2011
********************************************************/

#include <iostream>
#include <cstdio>
#include <cstdlib>
#include <cstring>
#include <cctype>
#include "xprb_cpp.h"

using namespace std;
using namespace ::dashoptimization;

#define MAXNUM 7                   // Max. number of different assets
#define MAXRISK 1/3              // Max. investment into high-risk values
#define MINREG 0,2                 // Min. investment per geogr. region
#define MAXREG 0,5                 // Max. investment per geogr. region
#define MAXSEC 0,25                // Max. investment per ind. sector
#define MAXVAL 0,2                 // Max. investment per share
#define MINVAL 0,1                 // Min. investment per share

#define DATAFILE "folio10.cdat"    // File with problem data
#define MAXENTRIES 10000


int NSHARES;                       // Number of shares
int NRISK;                         // Number of high-risk shares
int NREGIONS;                      // Number of geographical regions
int NTYPES;                        // Number of share types

double *RET;                       // Estimated return in investment
int *RISK;                         // High-risk values among shares
char **LOC;                        // Geogr. region of shares
char **SECT;                        // Industry sector of shares

char **SHARES_n;
char **REGIONS_n;
char **TYPES_n;

#include "readfoliodata.c_"


int main(int argc, char **argv)
{
 int s,r,t;
 XPRBprob p("FolioMIP3");          // Initialize a new problem in BCL
 XPRBexpr Risk,Return,Cap,Num;
 XPRBexpr *MinReg, *MaxReg, *LimSec, LinkL, LinkU;
 XPRBvar *frac;                    // Fraction of capital used per share
 XPRBvar *buy;                     // 1 if asset is in portfolio, 0 otherwise

 readdata(DATAFILE);               // Data input from file

// Create the decision variables (including upper bounds for `frac')
 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 for(s=0;s<NSHARES;s++) Return +=RET[s]*frac[s]; Set the objective function Limit percentage of high-risk values Risk <=MAXRISK); Limits on geographical distribution MinReg=new MaxReg=new for(r=0;r<NREGIONS;r++)>0)
   {
    MinReg[r] += frac[s];
    MaxReg[r] += frac[s];
   }
  p.newCtr(MinReg[r] >= MINREG);
  p.newCtr(MaxReg[r] <= MAXREG);
 }

// Diversification across industry sectors
 LimSec = new XPRBexpr[NTYPES];
 for(t=0;t<NTYPES;t++) for(s=0;s<NSHARES;s++)>0) LimSec[t] += frac[s];
  p.newCtr(LimSec[t] <= MAXSEC);
 }

// 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>= MINVAL*buy[s]);
 }

// Solve the problem
 p.setSense(XPRB_MAXIM);
 p.mipOptimize("");


 char *MIPSTATUS[] = {"not loaded", "not optimized", "LP optimized",
		      "unfinished (no solution)",
		      "unfinished (solution found)", "infeasible", "optimal",
                      "unbounded"};

 cout << "Problem status: " << MIPSTATUS[p.getMIPStat()] << endl;


// Solution printing
 cout << "Total return: " << p.getObjVal() << endl;
 for(s=0;s<NSHARES;s++)
  if(buy[s].getSol()>0,5)
   cout << SHARES_n[s] << ": " << frac[s].getSol()*100 << "% (" << buy[s].getSol()
        << ")" << endl;

 return 0;
}