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### Poolsearch.java

/* Copyright 2016, Gurobi Optimization, Inc. */

/* We find alternative epsilon-optimal solutions to a given knapsack
problem by using PoolSearchMode */

import gurobi.*;

public class Poolsearch {

public static void main(String[] args) {

try{
// Sample data
int groundSetSize = 10;
double objCoef[] = new double[] {32, 32, 15, 15, 6, 6, 1, 1, 1, 1};
double knapsackCoef[] = new double[] {16, 16,  8,  8, 4, 4, 2, 2, 1, 1};
double Budget = 33;
int e, status, nSolutions;

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

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

// Initialize decision variables for ground set:
// x[e] == 1 if element e is chosen
model.set(GRB.DoubleAttr.Obj, Elem, objCoef, 0, groundSetSize);

for (e = 0; e < groundSetSize; e++) {
Elem[e].set(GRB.StringAttr.VarName, "El" + String.valueOf(e));
}

// 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, 1024);

// Limit the search space by setting a gap for the worst possible solution that will be accepted
model.set(GRB.DoubleParam.PoolGap, 0.10);

// do a systematic search for the k-best solutions
model.set(GRB.IntParam.PoolSearchMode, 2);

// save problem
model.write("Poolsearch.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.print("\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
for (e = 0; e < nSolutions; e++) {
model.set(GRB.IntParam.SolutionNumber, e);
System.out.print(model.get(GRB.DoubleAttr.PoolObjVal) +  " ");
if (e%15 == 14) System.out.println();
}
System.out.println();

// print fourth best set if available
if (nSolutions >= 4) {
model.set(GRB.IntParam.SolutionNumber, 3);

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

model.dispose();
env.dispose();
} catch (GRBException e) {
System.out.println("Error code: " + e.getErrorCode() + ". " +
e.getMessage());
}
}

}


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