// Copyright 2010-2024 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. package com.google.ortools.algorithms; import static org.junit.jupiter.api.Assertions.assertEquals; import static org.junit.jupiter.api.Assertions.assertNotNull; import com.google.ortools.Loader; import org.junit.jupiter.api.BeforeEach; import org.junit.jupiter.api.Test; /** Test the Knapsack solver java interface. */ public final class KnapsackSolverTest { @BeforeEach public void setUp() { Loader.loadNativeLibraries(); } private long runKnapsackSolver(final KnapsackSolver.SolverType solverType, final long[] profits, final long[][] weights, final long[] capacities) { final KnapsackSolver solver = new KnapsackSolver(solverType, "test"); assertNotNull(solver); solver.init(profits, weights, capacities); return solver.solve(); } private void solveKnapsackProblem(final long[] profits, final long[][] weights, final long[] capacities, final long optimalProfit) { final int maxNumberOfItemsForBruteForce = 20; final int maxNumberOfItemsForDivideAndConquer = 32; final int maxNumberOfItemsFor64ItemsSolver = 64; { final long profit = runKnapsackSolver( KnapsackSolver.SolverType.KNAPSACK_MULTIDIMENSION_BRANCH_AND_BOUND_SOLVER, profits, weights, capacities); assertEquals(optimalProfit, profit); } // Other solvers don't support multidimension models. if (weights.length > 1) { return; } final int numOfItems = profits.length; if (numOfItems <= maxNumberOfItemsForBruteForce) { final long profit = runKnapsackSolver( KnapsackSolver.SolverType.KNAPSACK_BRUTE_FORCE_SOLVER, profits, weights, capacities); assertEquals(optimalProfit, profit); } if (numOfItems <= maxNumberOfItemsForDivideAndConquer) { final long profit = runKnapsackSolver(KnapsackSolver.SolverType.KNAPSACK_DIVIDE_AND_CONQUER_SOLVER, profits, weights, capacities); assertEquals(optimalProfit, profit); } { final long profit = runKnapsackSolver(KnapsackSolver.SolverType.KNAPSACK_DYNAMIC_PROGRAMMING_SOLVER, profits, weights, capacities); assertEquals(optimalProfit, profit); } if (numOfItems <= maxNumberOfItemsFor64ItemsSolver) { final long profit = runKnapsackSolver( KnapsackSolver.SolverType.KNAPSACK_64ITEMS_SOLVER, profits, weights, capacities); assertEquals(optimalProfit, profit); } } @Test public void testSolveOneDimension() { final long[] profits = {1, 2, 3, 4, 5, 6, 7, 8, 9}; final long[][] weights = {{1, 2, 3, 4, 5, 6, 7, 8, 9}}; final long[] capacities = {34}; final long optimalProfit = 34; solveKnapsackProblem(profits, weights, capacities, optimalProfit); } @Test public void testSolveTwoDimensions() { final long[] profits = {1, 2, 3, 4, 5, 6, 7, 8, 9}; final long[][] weights = {{1, 2, 3, 4, 5, 6, 7, 8, 9}, {1, 1, 1, 1, 1, 1, 1, 1, 1}}; final long[] capacities = {34, 4}; final long optimalProfit = 30; solveKnapsackProblem(profits, weights, capacities, optimalProfit); } @Test public void testSolveBigOneDimension() { final long[] profits = {360, 83, 59, 130, 431, 67, 230, 52, 93, 125, 670, 892, 600, 38, 48, 147, 78, 256, 63, 17, 120, 164, 432, 35, 92, 110, 22, 42, 50, 323, 514, 28, 87, 73, 78, 15, 26, 78, 210, 36, 85, 189, 274, 43, 33, 10, 19, 389, 276, 312}; final long[][] weights = {{7, 0, 30, 22, 80, 94, 11, 81, 70, 64, 59, 18, 0, 36, 3, 8, 15, 42, 9, 0, 42, 47, 52, 32, 26, 48, 55, 6, 29, 84, 2, 4, 18, 56, 7, 29, 93, 44, 71, 3, 86, 66, 31, 65, 0, 79, 20, 65, 52, 13}}; final long[] capacities = {850}; final long optimalProfit = 7534; solveKnapsackProblem(profits, weights, capacities, optimalProfit); } }