#region License Information /* HeuristicLab * Copyright (C) Heuristic and Evolutionary Algorithms Laboratory (HEAL) * * This file is part of HeuristicLab. * * HeuristicLab is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * HeuristicLab is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with HeuristicLab. If not, see . */ #endregion using System.IO; using System.Linq; using HEAL.Attic; using HeuristicLab.Algorithms.LocalSearch; using HeuristicLab.Data; using HeuristicLab.Encodings.BinaryVectorEncoding; using HeuristicLab.Problems.Knapsack; using Microsoft.VisualStudio.TestTools.UnitTesting; namespace HeuristicLab.Tests { [TestClass] public class LocalSearchKnapsackSampleTest { private const string SampleFileName = "LS_Knapsack"; private static readonly ProtoBufSerializer serializer = new ProtoBufSerializer(); [TestMethod] [TestCategory("Samples.Create")] [TestProperty("Time", "medium")] public void CreateLocalSearchKnapsackSampleTest() { var ls = CreateLocalSearchKnapsackSample(); string path = Path.Combine(SamplesUtils.SamplesDirectory, SampleFileName + SamplesUtils.SampleFileExtension); serializer.Serialize(ls, path); } [TestMethod] [TestCategory("Samples.Execute")] [TestProperty("Time", "medium")] public void RunLocalSearchKnapsackSampleTest() { var ls = CreateLocalSearchKnapsackSample(); ls.SetSeedRandomly.Value = false; SamplesUtils.RunAlgorithm(ls); Assert.AreEqual(345, SamplesUtils.GetDoubleResult(ls, "BestQuality")); Assert.AreEqual(340.70731707317071, SamplesUtils.GetDoubleResult(ls, "CurrentAverageQuality")); Assert.AreEqual(337, SamplesUtils.GetDoubleResult(ls, "CurrentWorstQuality")); Assert.AreEqual(82000, SamplesUtils.GetIntResult(ls, "EvaluatedMoves")); } private LocalSearch CreateLocalSearchKnapsackSample() { LocalSearch ls = new LocalSearch(); #region Problem Configuration KnapsackProblem problem = new KnapsackProblem(); problem.BestKnownQuality = new DoubleValue(362); problem.BestKnownSolution = new HeuristicLab.Encodings.BinaryVectorEncoding.BinaryVector(new bool[] { true , false, false, true , true , true , true , true , false, true , true , true , true , true , true , false, true , false, true , true , false, true , true , false, true , false, true , true , true , false, true , true , false, true , true , false, true , false, true , true , true , true , true , true , true , true , true , true , true , true , true , false, true , false, false, true , true , false, true , true , true , true , true , true , true , true , false, true , false, true , true , true , true , false, true , true , true , true , true , true , true , true}); problem.EvaluatorParameter.Value = new KnapsackEvaluator(); problem.SolutionCreatorParameter.Value = new RandomBinaryVectorCreator(); problem.KnapsackCapacity.Value = 297; problem.Maximization.Value = true; problem.Penalty.Value = 1; problem.Values = new IntArray(new int[] { 6, 1, 1, 6, 7, 8, 7, 4, 2, 5, 2, 6, 7, 8, 7, 1, 7, 1, 9, 4, 2, 6, 5, 3, 5, 3, 3, 6, 5, 2, 4, 9, 4, 5, 7, 1, 4, 3, 5, 5, 8, 3, 6, 7, 3, 9, 7, 7, 5, 5, 7, 1, 4, 4, 3, 9, 5, 1, 6, 2, 2, 6, 1, 6, 5, 4, 4, 7, 1, 8, 9, 9, 7, 4, 3, 8, 7, 5, 7, 4, 4, 5}); problem.Weights = new IntArray(new int[] { 1, 9, 3, 6, 5, 3, 8, 1, 7, 4, 2, 1, 2, 7, 9, 9, 8, 4, 9, 2, 4, 8, 3, 7, 5, 7, 5, 5, 1, 9, 8, 7, 8, 9, 1, 3, 3, 8, 8, 5, 1, 2, 4, 3, 6, 9, 4, 4, 9, 7, 4, 5, 1, 9, 7, 6, 7, 4, 7, 1, 2, 1, 2, 9, 8, 6, 8, 4, 7, 6, 7, 5, 3, 9, 4, 7, 4, 6, 1, 2, 5, 4}); problem.Name = "Knapsack Problem"; problem.Description = "Represents a Knapsack problem."; #endregion #region Algorithm Configuration ls.Name = "Local Search - Knapsack"; ls.Description = "A local search algorithm that solves a randomly generated Knapsack problem"; ls.Problem = problem; ls.MaximumIterations.Value = 1000; ls.MoveEvaluator = ls.MoveEvaluatorParameter.ValidValues .OfType() .Single(); ls.MoveGenerator = ls.MoveGeneratorParameter.ValidValues .OfType() .Single(); ls.MoveMaker = ls.MoveMakerParameter.ValidValues .OfType() .Single(); ls.SampleSize.Value = 100; ls.Seed.Value = 0; ls.SetSeedRandomly.Value = true; #endregion ls.Engine = new ParallelEngine.ParallelEngine(); return ls; } } }