126 lines
4.2 KiB
Java
126 lines
4.2 KiB
Java
// Copyright 2010-2021 Google LLC
|
|
// Licensed under the Apache License, Version 2.0 (the "License");
|
|
// you may not use this file except in compliance with the License.
|
|
// You may obtain a copy of the License at
|
|
//
|
|
// http://www.apache.org/licenses/LICENSE-2.0
|
|
//
|
|
// Unless required by applicable law or agreed to in writing, software
|
|
// distributed under the License is distributed on an "AS IS" BASIS,
|
|
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
// See the License for the specific language governing permissions and
|
|
// limitations under the License.
|
|
|
|
// [START program]
|
|
// Solve a multiple knapsack problem using a MIP solver.
|
|
package com.google.ortools.linearsolver.samples;
|
|
// [START import]
|
|
import com.google.ortools.Loader;
|
|
import com.google.ortools.linearsolver.MPConstraint;
|
|
import com.google.ortools.linearsolver.MPObjective;
|
|
import com.google.ortools.linearsolver.MPSolver;
|
|
import com.google.ortools.linearsolver.MPVariable;
|
|
import java.util.stream.IntStream;
|
|
// [END import]
|
|
|
|
/** Multiple knapsack problem. */
|
|
public class MultipleKnapsackMip {
|
|
public static void main(String[] args) {
|
|
Loader.loadNativeLibraries();
|
|
// Instantiate the data problem.
|
|
// [START data]
|
|
final double[] weights = {48, 30, 42, 36, 36, 48, 42, 42, 36, 24, 30, 30, 42, 36, 36};
|
|
final double[] values = {10, 30, 25, 50, 35, 30, 15, 40, 30, 35, 45, 10, 20, 30, 25};
|
|
final int numItems = weights.length;
|
|
final int[] allItems = IntStream.range(0, numItems).toArray();
|
|
|
|
final double[] binCapacities = {100, 100, 100, 100, 100};
|
|
final int numBins = binCapacities.length;
|
|
final int[] allBins = IntStream.range(0, numBins).toArray();
|
|
// [END data]
|
|
|
|
// [START solver]
|
|
// Create the linear solver with the SCIP backend.
|
|
MPSolver solver = MPSolver.createSolver("SCIP");
|
|
if (solver == null) {
|
|
System.out.println("Could not create solver SCIP");
|
|
return;
|
|
}
|
|
// [END solver]
|
|
|
|
// Variables.
|
|
// [START variables]
|
|
MPVariable[][] x = new MPVariable[numItems][numBins];
|
|
for (int i : allItems) {
|
|
for (int b : allBins) {
|
|
x[i][b] = solver.makeBoolVar("x_" + i + "_" + b);
|
|
}
|
|
}
|
|
// [END variables]
|
|
|
|
// Constraints.
|
|
// [START constraints]
|
|
// Each item is assigned to at most one bin.
|
|
for (int i : allItems) {
|
|
MPConstraint constraint = solver.makeConstraint(0, 1, "");
|
|
for (int b : allBins) {
|
|
constraint.setCoefficient(x[i][b], 1);
|
|
}
|
|
}
|
|
|
|
// The amount packed in each bin cannot exceed its capacity.
|
|
for (int b : allBins) {
|
|
MPConstraint constraint = solver.makeConstraint(0, binCapacities[b], "");
|
|
for (int i : allItems) {
|
|
constraint.setCoefficient(x[i][b], weights[i]);
|
|
}
|
|
}
|
|
// [END constraints]
|
|
|
|
// Objective.
|
|
// [START objective]
|
|
// Maximize total value of packed items.
|
|
MPObjective objective = solver.objective();
|
|
for (int i : allItems) {
|
|
for (int b : allBins) {
|
|
objective.setCoefficient(x[i][b], values[i]);
|
|
}
|
|
}
|
|
objective.setMaximization();
|
|
// [END objective]
|
|
|
|
// [START solve]
|
|
final MPSolver.ResultStatus status = solver.solve();
|
|
// [END solve]
|
|
|
|
// [START print_solution]
|
|
// Check that the problem has an optimal solution.
|
|
if (status == MPSolver.ResultStatus.OPTIMAL) {
|
|
System.out.println("Total packed value: " + objective.value());
|
|
double totalWeight = 0;
|
|
for (int b : allBins) {
|
|
double binWeight = 0;
|
|
double binValue = 0;
|
|
System.out.println("Bin " + b);
|
|
for (int i : allItems) {
|
|
if (x[i][b].solutionValue() == 1) {
|
|
System.out.println("Item " + i + " weight: " + weights[i] + " value: " + values[i]);
|
|
binWeight += weights[i];
|
|
binValue += values[i];
|
|
}
|
|
}
|
|
System.out.println("Packed bin weight: " + binWeight);
|
|
System.out.println("Packed bin value: " + binValue);
|
|
totalWeight += binWeight;
|
|
}
|
|
System.out.println("Total packed weight: " + totalWeight);
|
|
} else {
|
|
System.err.println("The problem does not have an optimal solution.");
|
|
}
|
|
// [END print_solution]
|
|
}
|
|
|
|
private MultipleKnapsackMip() {}
|
|
}
|
|
// [END program]
|