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Perform objective function parametrics on a MIP problem

Description
Perform objective function parametrics on a global problem. We take a production plan model and observe how the optimal value of the objective function changes as we vary BEN(3), the benefit per month from finishing Project 3. The program increments BEN(3) from 8 to 15, and for each of these values revises the objective coefficients of the variables x(3,t),t=1:2 and finds the best integer solution. Note that, for each t, the coefficient of x(3,t) is BEN(3)*(3-t) = BEN(3)*(6-t-4+1). The results are displayed on screen and the problem statistics stored in a log file.

objparams_java.zip[download all files]

Source Files
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GlobalObjectiveParametrics.java[download]

Data Files





GlobalObjectiveParametrics.java

/***********************************************************************
   Xpress Optimizer Examples
   =========================

   file GlobalObjectiveParametrics.java
   ```````````````
   Perform objective function parametrics on a global problem.
   (c) 2021-2024 Fair Isaac Corporation
***********************************************************************/

import com.dashoptimization.DefaultMessageListener;
import com.dashoptimization.XPRS;
import com.dashoptimization.XPRSprob;
import static com.dashoptimization.XPRSenumerations.ObjSense;

/** Perform objective function parametrics on a global problem.
 * We take a production plan model and observe how the optimal
 * value of the objective function changes as we vary
 * BEN(3), the benefit per month from finishing Project 3.
 * The program increments BEN(3) from 8 to 15, and for each of these
 * values revises the objective coefficients of the variables x(3,t),t=1:2
 * and finds the best integer solution. Note that, for each t, the
 * coefficient of x(3,t) is BEN(3)*(3-t) = BEN(3)*(6-t-4+1).
 * The results are displayed on screen and the problem statistics stored
 * in a log file.
 */
public class GlobalObjectiveParametrics {
    /** Run the example.
     * @param args If non-empty then <code>args[0]</code> is used as problem,
     *             otherwise "pplan" is used.
     */
    public static void main(String[] args) {
        String problem = args.length == 0 ? "../data/pplan" : args[0];
        if (args.length > 0)
            problem = args[0];
        String logFile = "GlobalObjectiveParametrics.log";

        try (XPRSprob prob = new XPRSprob(null);
             XPRSprob copy = new XPRSprob(null)) {
            // Delete and define log file
            new java.io.File(logFile).delete();
            prob.setLogFile(logFile);

            // Install default output: We only print warning and error messages.
            prob.addMessageListener(new DefaultMessageListener(null, System.err, System.err));

            // Read the problem file
            prob.readProb(problem);

            // Set the objective sense
            prob.chgObjSense(ObjSense.MAXIMIZE);

            // Get the number rows and columns
            int rows = prob.attributes().getRows();
            int cols = prob.attributes().getCols();

            // Get the column indices for x(3,t),t=1:2
            int[] x3 = new int[]{ prob.getIndex(2, "x___0301"),
                                  prob.getIndex(2, "x___0302") };

            // Allocate memory for the basis status arrays
            int[] rowStatus = new int[rows];
            int[] colStatus = new int[cols];

            System.out.printf("The results of the parameter changes on pplan are:%n%n");

            // Increment BEN(3) from 8 to 15
            for (int i = 8; i <= 15; ++i) {
                double ben3 = (double) i;

                // Revise the objective coefficients of x(3,t),t=1:2
                double[] newobj = new double[]{ ben3*(3.0-1.0),
                                                ben3*(3.0-2.0) };

                // Change the objective function
                prob.chgObj(2, x3, newobj);

                // Store the current matrix - as global will later change it
                copy.copyProb(prob);

                // Restore the previous optimal basis - for efficiency
                if (i > 8)
                    copy.loadBasis(rowStatus, colStatus);

                // Solve the root node relaxation
                copy.mipOptimize("l");

                // Get the optimal basis
                copy.getBasis(rowStatus, colStatus);

                // Search for an integer solution
                copy.mipOptimize();

                // Get, and then print, the objective value of the best integer solution
                double objval = copy.attributes().getMIPObjVal();
                System.out.printf("   BEN(3) = %2.0f; objective = %4.1f%n", ben3, objval);

            }

            System.out.println();
        }
    }
}

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