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

  file foliomip1.java
  ```````````````````
  Modeling a small LP problem
  to perform portfolio optimization.
   -- Limiting the total number of assets --

  (c) 2008-2023 Fair Isaac Corporation
      author: S.Heipcke, 2003, rev. Dec. 2011
********************************************************/

import com.dashoptimization.*;

public class foliomip1 {
    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 final String[] MIPSTATUS = {"not loaded", "not optimized",
                                       "LP optimized", "unfinished (no solution)",
                                       "unfinished (solution found)", "infeasible", "optimal",
                                       "unbounded"};

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

        try (XPRBprob p = new XPRBprob("FolioMIP1")) {  /* Initialize BCL and create a new problem */

            /* Create the decision variables */
            frac = new XPRBvar[NSHARES];
            buy = new XPRBvar[NSHARES];
            for(s=0;s<NSHARES;s++) {
                frac[s] = p.newVar("frac", XPRB.PL, 0, 0,3);
                buy[s] = p.newVar("buy", XPRB.BV);
            }

            /* Objective: total return */
            Return = new XPRBexpr();
            for(s=0;s<NSHARES;s++) Return.add(frac[s].mul(RET[s]));
            p.setObj(Return);                  /* Set the objective function */

            /* Limit the percentage of high-risk values */
            Risk = new XPRBexpr();
            for(s=0;s<NRISK;s++) Risk.add(frac[RISK[s]]);
            p.newCtr(Risk.lEql(1/3));

            /* Minimum amount of North-American values */
            Na = new XPRBexpr();
            for(s=0;s<NNA;s++) Na.add(frac[NA[s]]);
            p.newCtr(Na.gEql(0,5));

            /* Spend all the capital */
            Cap = new XPRBexpr();
            for(s=0;s<NSHARES;s++) Cap.add(frac[s]);
            p.newCtr(Cap.eql(1));

            /* Limit the total number of assets */
            Num = new XPRBexpr();
            for(s=0;s<NSHARES;s++) Num.add(buy[s]);
            p.newCtr(Num.lEql(MAXNUM));

            /* Linking the variables */
            for(s=0;s<NSHARES;s++) p.newCtr(frac[s].lEql(buy[s]));

            /* Solve the problem */
            p.setSense(XPRB.MAXIM);
            p.mipOptimize("");

            System.out.println("Problem status: " + MIPSTATUS[p.getMIPStat()]);

            /* Solution printing */
            System.out.println("Total return: " + p.getObjVal());
            for(s=0;s<NSHARES;s++)
                System.out.println(s + ": " + frac[s].getSol()*100 + "% (" +
                                   buy[s].getSol() + ")");

        }
    }
}