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### Multiobj.java

/* Copyright 2023, Gurobi Optimization, LLC */

/* Want to cover three different sets but subject to a common budget of
elements allowed to be used. However, the sets have different priorities to
be covered; and we tackle this by using multi-objective optimization. */

import gurobi.*;

public class Multiobj {
public static void main(String[] args) {

try {
// Sample data
int groundSetSize = 20;
int nSubsets      = 4;
int Budget        = 12;
double Set[][] = new double[][]
{ { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
{ 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1 },
{ 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0 },
{ 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0 } };
int    SetObjPriority[] = new int[] {3, 2, 2, 1};
double SetObjWeight[]   = new double[] {1.0, 0.25, 1.25, 1.0};
int e, i, status, nSolutions;

// Create environment
GRBEnv env = new GRBEnv("Multiobj.log");

// Create initial model
GRBModel model = new GRBModel(env);
model.set(GRB.StringAttr.ModelName, "Multiobj");

// Initialize decision variables for ground set:
// x[e] == 1 if element e is chosen for the covering.
for (e = 0; e < groundSetSize; e++) {
String vname = "El" + String.valueOf(e);
Elem[e].set(GRB.StringAttr.VarName, vname);
}

// Constraint: limit total number of elements to be picked to be at most
// Budget
GRBLinExpr lhs = new GRBLinExpr();
for (e = 0; e < groundSetSize; e++) {
}

// Set global sense for ALL objectives
model.set(GRB.IntAttr.ModelSense, GRB.MAXIMIZE);

// Limit how many solutions to collect
model.set(GRB.IntParam.PoolSolutions, 100);

// Set and configure i-th objective
for (i = 0; i < nSubsets; i++) {
GRBLinExpr objn = new GRBLinExpr();
String vname = "Set" + String.valueOf(i);

for (e = 0; e < groundSetSize; e++)

model.setObjectiveN(objn, i, SetObjPriority[i], SetObjWeight[i],
1.0 + i, 0.01, vname);
}

// Save problem
model.write("Multiobj.lp");

// Optimize
model.optimize();

// Status checking
status = model.get(GRB.IntAttr.Status);

if (status == GRB.INF_OR_UNBD ||
status == GRB.INFEASIBLE  ||
status == GRB.UNBOUNDED     ) {
System.out.println("The model cannot be solved " +
"because it is infeasible or unbounded");
System.exit(1);
}
if (status != GRB.OPTIMAL) {
System.out.println("Optimization was stopped with status " + status);
System.exit(1);
}

// Print best selected set
System.out.println("Selected elements in best solution:");
System.out.println("\t");
for (e = 0; e < groundSetSize; e++) {
if (Elem[e].get(GRB.DoubleAttr.X) < .9) continue;
System.out.print(" El" + e);
}
System.out.println();

// Print number of solutions stored
nSolutions = model.get(GRB.IntAttr.SolCount);
System.out.println("Number of solutions found: " + nSolutions);

// Print objective values of solutions
if (nSolutions > 10) nSolutions = 10;
System.out.println("Objective values for first " + nSolutions);
System.out.println(" solutions:");
for (i = 0; i < nSubsets; i++) {
model.set(GRB.IntParam.ObjNumber, i);

System.out.print("\tSet" + i);
for (e = 0; e < nSolutions; e++) {
System.out.print(" ");
model.set(GRB.IntParam.SolutionNumber, e);
double val = model.get(GRB.DoubleAttr.ObjNVal);
System.out.print("      " + val);
}
System.out.println();
}
model.dispose();
env.dispose();
} catch (GRBException e) {
System.out.println("Error code = " + e.getErrorCode());
System.out.println(e.getMessage());
}
}
}


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