[6544] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[7259] | 3 | * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[6544] | 4 | *
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| 5 | * This file is part of HeuristicLab.
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| 6 | *
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| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 8 | * it under the terms of the GNU General Public License as published by
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| 9 | * the Free Software Foundation, either version 3 of the License, or
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| 10 | * (at your option) any later version.
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| 11 | *
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| 12 | * HeuristicLab is distributed in the hope that it will be useful,
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| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 15 | * GNU General Public License for more details.
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| 16 | *
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| 17 | * You should have received a copy of the GNU General Public License
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| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 19 | */
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| 20 | #endregion
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| 21 |
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| 22 | using System;
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[6441] | 23 | using System.Linq;
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[6544] | 24 | using System.Threading;
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| 25 | using HeuristicLab.Algorithms.EvolutionStrategy;
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[6441] | 26 | using HeuristicLab.Algorithms.GeneticAlgorithm;
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[6544] | 27 | using HeuristicLab.Algorithms.LocalSearch;
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| 28 | using HeuristicLab.Algorithms.ParticleSwarmOptimization;
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| 29 | using HeuristicLab.Algorithms.SimulatedAnnealing;
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| 30 | using HeuristicLab.Algorithms.TabuSearch;
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| 31 | using HeuristicLab.Algorithms.VariableNeighborhoodSearch;
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[6441] | 32 | using HeuristicLab.Data;
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[6544] | 33 | using HeuristicLab.Encodings.BinaryVectorEncoding;
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| 34 | using HeuristicLab.Encodings.PermutationEncoding;
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| 35 | using HeuristicLab.Encodings.RealVectorEncoding;
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[6441] | 36 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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| 37 | using HeuristicLab.Optimization;
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[6544] | 38 | using HeuristicLab.Optimization.Operators;
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[6441] | 39 | using HeuristicLab.ParallelEngine;
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[6544] | 40 | using HeuristicLab.Persistence.Default.Xml;
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| 41 | using HeuristicLab.Problems.ArtificialAnt;
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[6441] | 42 | using HeuristicLab.Problems.DataAnalysis;
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| 43 | using HeuristicLab.Problems.DataAnalysis.Symbolic;
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| 44 | using HeuristicLab.Problems.DataAnalysis.Symbolic.Classification;
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[6544] | 45 | using HeuristicLab.Problems.DataAnalysis.Symbolic.Regression;
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[8195] | 46 | using HeuristicLab.Problems.Instances;
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[7849] | 47 | using HeuristicLab.Problems.Instances.DataAnalysis;
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[7558] | 48 | using HeuristicLab.Problems.Instances.TSPLIB;
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[8195] | 49 | using HeuristicLab.Problems.Instances.VehicleRouting;
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[6544] | 50 | using HeuristicLab.Problems.Knapsack;
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| 51 | using HeuristicLab.Problems.TestFunctions;
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[6441] | 52 | using HeuristicLab.Problems.TravelingSalesman;
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| 53 | using HeuristicLab.Problems.VehicleRouting;
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[6544] | 54 | using HeuristicLab.Problems.VehicleRouting.Encodings.General;
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[6441] | 55 | using HeuristicLab.Problems.VehicleRouting.Encodings.Potvin;
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[7900] | 56 | using HeuristicLab.Problems.VehicleRouting.ProblemInstances;
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[6544] | 57 | using HeuristicLab.Selection;
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| 58 | using Microsoft.VisualStudio.TestTools.UnitTesting;
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[6441] | 59 |
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[7900] | 60 |
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[6441] | 61 | namespace HeuristicLab_33.Tests {
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| 62 | [TestClass]
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[6844] | 63 | [DeploymentItem(@"HeuristicLab-3.3/Resources/C101.opt.txt")]
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| 64 | [DeploymentItem(@"HeuristicLab-3.3/Resources/C101.txt")]
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[6476] | 65 | public class SamplesTest {
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| 66 | #region GA
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[6468] | 67 | #region TSP
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[6441] | 68 | [TestMethod]
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[6476] | 69 | public void CreateGaTspSampleTest() {
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| 70 | var ga = CreateGaTspSample();
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[6468] | 71 | XmlGenerator.Serialize(ga, "../../GA_TSP.hl");
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| 72 | }
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| 73 | [TestMethod]
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[6476] | 74 | public void RunGaTspSampleTest() {
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| 75 | var ga = CreateGaTspSample();
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[6468] | 76 | ga.SetSeedRandomly.Value = false;
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| 77 | RunAlgorithm(ga);
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| 78 | Assert.AreEqual(12332, GetDoubleResult(ga, "BestQuality"));
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| 79 | Assert.AreEqual(13123.2, GetDoubleResult(ga, "CurrentAverageQuality"));
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| 80 | Assert.AreEqual(14538, GetDoubleResult(ga, "CurrentWorstQuality"));
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| 81 | Assert.AreEqual(99100, GetIntResult(ga, "EvaluatedSolutions"));
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| 82 | }
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| 83 |
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[6476] | 84 | private GeneticAlgorithm CreateGaTspSample() {
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[6441] | 85 | GeneticAlgorithm ga = new GeneticAlgorithm();
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[6544] | 86 | #region Problem Configuration
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[7558] | 87 | var provider = new TSPLIBTSPInstanceProvider();
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| 88 | var instance = provider.GetDataDescriptors().Where(x => x.Name == "ch130").Single();
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[6441] | 89 | TravelingSalesmanProblem tspProblem = new TravelingSalesmanProblem();
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[7558] | 90 | tspProblem.Load(provider.LoadData(instance));
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[6441] | 91 | tspProblem.UseDistanceMatrix.Value = true;
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| 92 | #endregion
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[6544] | 93 | #region Algorithm Configuration
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[6441] | 94 | ga.Name = "Genetic Algorithm - TSP";
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| 95 | ga.Description = "A genetic algorithm which solves the \"ch130\" traveling salesman problem (imported from TSPLIB)";
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| 96 | ga.Problem = tspProblem;
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| 97 | ConfigureGeneticAlgorithmParameters<ProportionalSelector, OrderCrossover2, InversionManipulator>(
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| 98 | ga, 100, 1, 1000, 0.05);
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| 99 | #endregion
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[6468] | 100 | return ga;
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| 101 | }
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| 102 | #endregion
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| 103 | #region VRP
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| 104 | [TestMethod]
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[6476] | 105 | public void CreateGaVrpSampleTest() {
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| 106 | var ga = CreateGaVrpSample();
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[6468] | 107 | XmlGenerator.Serialize(ga, "../../GA_VRP.hl");
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| 108 | }
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[6441] | 109 |
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[6468] | 110 | [TestMethod]
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[6476] | 111 | public void RunGaVrpSampleTest() {
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| 112 | var ga = CreateGaVrpSample();
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[6468] | 113 | ga.SetSeedRandomly.Value = false;
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[6441] | 114 | RunAlgorithm(ga);
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[7900] | 115 | Assert.AreEqual(1828.9368669428338, GetDoubleResult(ga, "BestQuality"));
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| 116 | Assert.AreEqual(1830.1444308908331, GetDoubleResult(ga, "CurrentAverageQuality"));
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| 117 | Assert.AreEqual(1871.7128510304112, GetDoubleResult(ga, "CurrentWorstQuality"));
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[6468] | 118 | Assert.AreEqual(99100, GetIntResult(ga, "EvaluatedSolutions"));
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[6441] | 119 | }
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[6468] | 120 |
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[6476] | 121 | private GeneticAlgorithm CreateGaVrpSample() {
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[6441] | 122 | GeneticAlgorithm ga = new GeneticAlgorithm();
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[6544] | 123 | #region Problem Configuration
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[6441] | 124 | VehicleRoutingProblem vrpProblem = new VehicleRoutingProblem();
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| 125 |
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[7900] | 126 | SolomonFormatInstanceProvider instanceProvider = new SolomonInstanceProvider();
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[8195] | 127 | IVRPData data = instanceProvider.Import("C101.txt", "C101.opt.txt");
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[7900] | 128 | vrpProblem.Load(data);
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[6441] | 129 | vrpProblem.Name = "C101 VRP (imported from Solomon)";
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| 130 | vrpProblem.Description = "Represents a Vehicle Routing Problem.";
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[7900] | 131 | CVRPTWProblemInstance instance = vrpProblem.ProblemInstance as CVRPTWProblemInstance;
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| 132 | instance.DistanceFactor.Value = 1;
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| 133 | instance.FleetUsageFactor.Value = 100;
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| 134 | instance.OverloadPenalty.Value = 100;
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| 135 | instance.TardinessPenalty.Value = 100;
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| 136 | instance.TimeFactor.Value = 0;
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[6441] | 137 | vrpProblem.MaximizationParameter.Value.Value = false;
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[7900] | 138 | instance.UseDistanceMatrix.Value = true;
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| 139 | instance.Vehicles.Value = 25;
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[6441] | 140 | #endregion
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[6544] | 141 | #region Algorithm Configuration
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[6441] | 142 | ga.Name = "Genetic Algorithm - VRP";
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| 143 | ga.Description = "A genetic algorithm which solves the \"C101\" vehicle routing problem (imported from Solomon)";
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| 144 | ga.Problem = vrpProblem;
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| 145 | ConfigureGeneticAlgorithmParameters<TournamentSelector, MultiVRPSolutionCrossover, MultiVRPSolutionManipulator>(
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| 146 | ga, 100, 1, 1000, 0.05, 3);
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| 147 |
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| 148 | var xOver = (MultiVRPSolutionCrossover)ga.Crossover;
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| 149 | foreach (var op in xOver.Operators) {
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| 150 | xOver.Operators.SetItemCheckedState(op, false);
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| 151 | }
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| 152 | xOver.Operators.SetItemCheckedState(xOver.Operators
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| 153 | .OfType<PotvinRouteBasedCrossover>()
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| 154 | .Single(), true);
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| 155 | xOver.Operators.SetItemCheckedState(xOver.Operators
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| 156 | .OfType<PotvinSequenceBasedCrossover>()
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| 157 | .Single(), true);
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| 158 |
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| 159 | var manipulator = (MultiVRPSolutionManipulator)ga.Mutator;
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| 160 | foreach (var op in manipulator.Operators) {
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| 161 | manipulator.Operators.SetItemCheckedState(op, false);
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| 162 | }
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| 163 | manipulator.Operators.SetItemCheckedState(manipulator.Operators
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| 164 | .OfType<PotvinOneLevelExchangeMainpulator>()
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| 165 | .Single(), true);
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| 166 | manipulator.Operators.SetItemCheckedState(manipulator.Operators
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| 167 | .OfType<PotvinTwoLevelExchangeManipulator>()
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| 168 | .Single(), true);
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| 169 | #endregion
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[6468] | 170 | return ga;
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| 171 | }
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| 172 | #endregion
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| 173 | #region ArtificialAnt
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| 174 | [TestMethod]
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[6476] | 175 | public void CreateGpArtificialAntSampleTest() {
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| 176 | var ga = CreateGpArtificialAntSample();
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[6468] | 177 | XmlGenerator.Serialize(ga, "../../SGP_SantaFe.hl");
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| 178 | }
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| 179 |
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| 180 | [TestMethod]
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[6476] | 181 | public void RunGpArtificialAntSampleTest() {
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[6928] | 182 | var ga = CreateGpArtificialAntSample();
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[6468] | 183 | ga.SetSeedRandomly.Value = false;
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[6441] | 184 | RunAlgorithm(ga);
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[8335] | 185 | Assert.AreEqual(81, GetDoubleResult(ga, "BestQuality"));
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| 186 | Assert.AreEqual(48.19, GetDoubleResult(ga, "CurrentAverageQuality"));
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[6822] | 187 | Assert.AreEqual(0, GetDoubleResult(ga, "CurrentWorstQuality"));
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| 188 | Assert.AreEqual(50950, GetIntResult(ga, "EvaluatedSolutions"));
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[6441] | 189 | }
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| 190 |
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[6476] | 191 | public GeneticAlgorithm CreateGpArtificialAntSample() {
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[6441] | 192 | GeneticAlgorithm ga = new GeneticAlgorithm();
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[6544] | 193 | #region Problem Configuration
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[6441] | 194 | ArtificialAntProblem antProblem = new ArtificialAntProblem();
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| 195 | antProblem.BestKnownQuality.Value = 89;
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| 196 | antProblem.MaxExpressionDepth.Value = 10;
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| 197 | antProblem.MaxExpressionLength.Value = 100;
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| 198 | antProblem.MaxFunctionArguments.Value = 3;
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| 199 | antProblem.MaxFunctionDefinitions.Value = 3;
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| 200 | antProblem.MaxTimeSteps.Value = 600;
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| 201 | #endregion
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[6544] | 202 | #region Algorithm Configuration
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[6441] | 203 | ga.Name = "Genetic Programming - Artificial Ant";
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| 204 | ga.Description = "A standard genetic programming algorithm to solve the artificial ant problem (Santa-Fe trail)";
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| 205 | ga.Problem = antProblem;
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| 206 | ConfigureGeneticAlgorithmParameters<TournamentSelector, SubtreeCrossover, MultiSymbolicExpressionTreeArchitectureManipulator>(
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[6474] | 207 | ga, 1000, 1, 50, 0.15, 5);
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[6441] | 208 | var mutator = (MultiSymbolicExpressionTreeArchitectureManipulator)ga.Mutator;
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| 209 | mutator.Operators.SetItemCheckedState(mutator.Operators
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| 210 | .OfType<FullTreeShaker>()
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| 211 | .Single(), false);
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| 212 | mutator.Operators.SetItemCheckedState(mutator.Operators
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| 213 | .OfType<OnePointShaker>()
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| 214 | .Single(), false);
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[6442] | 215 | mutator.Operators.SetItemCheckedState(mutator.Operators
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| 216 | .OfType<ArgumentDeleter>()
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| 217 | .Single(), false);
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| 218 | mutator.Operators.SetItemCheckedState(mutator.Operators
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| 219 | .OfType<SubroutineDeleter>()
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| 220 | .Single(), false);
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[6441] | 221 | #endregion
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[6468] | 222 | return ga;
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| 223 | }
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| 224 | #endregion
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[6544] | 225 | #region Symbolic Regression
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[6468] | 226 | [TestMethod]
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[6476] | 227 | public void CreateGpSymbolicRegressionSampleTest() {
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| 228 | var ga = CreateGpSymbolicRegressionSample();
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[6468] | 229 | XmlGenerator.Serialize(ga, "../../SGP_SymbReg.hl");
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| 230 | }
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| 231 | [TestMethod]
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[6476] | 232 | public void RunGpSymbolicRegressionSampleTest() {
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| 233 | var ga = CreateGpSymbolicRegressionSample();
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[6468] | 234 | ga.SetSeedRandomly.Value = false;
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[6441] | 235 | RunAlgorithm(ga);
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[8335] | 236 | Assert.AreEqual(0.84966698918060757, GetDoubleResult(ga, "BestQuality"), 1E-8);
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| 237 | Assert.AreEqual(0.59815405391256571, GetDoubleResult(ga, "CurrentAverageQuality"), 1E-8);
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[7662] | 238 | Assert.AreEqual(0, GetDoubleResult(ga, "CurrentWorstQuality"), 1E-8);
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[6822] | 239 | Assert.AreEqual(50950, GetIntResult(ga, "EvaluatedSolutions"));
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[6441] | 240 | }
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| 241 |
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[6476] | 242 | private GeneticAlgorithm CreateGpSymbolicRegressionSample() {
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[6441] | 243 | GeneticAlgorithm ga = new GeneticAlgorithm();
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[6544] | 244 | #region Problem Configuration
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[6441] | 245 | SymbolicRegressionSingleObjectiveProblem symbRegProblem = new SymbolicRegressionSingleObjectiveProblem();
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| 246 | symbRegProblem.Name = "Tower Symbolic Regression Problem";
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| 247 | symbRegProblem.Description = "Tower Dataset (downloaded from: http://vanillamodeling.com/realproblems.html)";
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[7849] | 248 | RegressionRealWorldInstanceProvider provider = new RegressionRealWorldInstanceProvider();
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[7863] | 249 | var instance = provider.GetDataDescriptors().Where(x => x.Name.Equals("TowerData")).Single();
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[7823] | 250 | var towerProblemData = (RegressionProblemData)provider.LoadData(instance);
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[6441] | 251 | towerProblemData.TargetVariableParameter.Value = towerProblemData.TargetVariableParameter.ValidValues
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| 252 | .First(v => v.Value == "towerResponse");
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| 253 | towerProblemData.InputVariables.SetItemCheckedState(
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| 254 | towerProblemData.InputVariables.Single(x => x.Value == "x1"), true);
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| 255 | towerProblemData.InputVariables.SetItemCheckedState(
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| 256 | towerProblemData.InputVariables.Single(x => x.Value == "x7"), false);
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| 257 | towerProblemData.InputVariables.SetItemCheckedState(
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| 258 | towerProblemData.InputVariables.Single(x => x.Value == "x11"), false);
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| 259 | towerProblemData.InputVariables.SetItemCheckedState(
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| 260 | towerProblemData.InputVariables.Single(x => x.Value == "x16"), false);
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| 261 | towerProblemData.InputVariables.SetItemCheckedState(
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| 262 | towerProblemData.InputVariables.Single(x => x.Value == "x21"), false);
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| 263 | towerProblemData.InputVariables.SetItemCheckedState(
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| 264 | towerProblemData.InputVariables.Single(x => x.Value == "x25"), false);
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| 265 | towerProblemData.InputVariables.SetItemCheckedState(
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| 266 | towerProblemData.InputVariables.Single(x => x.Value == "towerResponse"), false);
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| 267 | towerProblemData.TrainingPartition.Start = 0;
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| 268 | towerProblemData.TrainingPartition.End = 4000;
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| 269 | towerProblemData.TestPartition.Start = 4000;
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| 270 | towerProblemData.TestPartition.End = 4999;
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| 271 | towerProblemData.Name = "Data imported from towerData.txt";
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| 272 | towerProblemData.Description = "Chemical concentration at top of distillation tower, dataset downloaded from: http://vanillamodeling.com/realproblems.html, best R² achieved with nu-SVR = 0.97";
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| 273 | symbRegProblem.ProblemData = towerProblemData;
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| 274 |
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| 275 | // configure grammar
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| 276 | var grammar = new TypeCoherentExpressionGrammar();
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[6999] | 277 | grammar.ConfigureAsDefaultRegressionGrammar();
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[6441] | 278 | grammar.Symbols.OfType<VariableCondition>().Single().InitialFrequency = 0.0;
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| 279 | var varSymbol = grammar.Symbols.OfType<Variable>().Where(x => !(x is LaggedVariable)).Single();
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| 280 | varSymbol.WeightMu = 1.0;
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| 281 | varSymbol.WeightSigma = 1.0;
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| 282 | varSymbol.WeightManipulatorMu = 0.0;
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| 283 | varSymbol.WeightManipulatorSigma = 0.05;
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| 284 | varSymbol.MultiplicativeWeightManipulatorSigma = 0.03;
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| 285 | var constSymbol = grammar.Symbols.OfType<Constant>().Single();
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| 286 | constSymbol.MaxValue = 20;
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| 287 | constSymbol.MinValue = -20;
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| 288 | constSymbol.ManipulatorMu = 0.0;
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| 289 | constSymbol.ManipulatorSigma = 1;
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| 290 | constSymbol.MultiplicativeManipulatorSigma = 0.03;
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| 291 | symbRegProblem.SymbolicExpressionTreeGrammar = grammar;
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| 292 |
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| 293 | // configure remaining problem parameters
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| 294 | symbRegProblem.BestKnownQuality.Value = 0.97;
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| 295 | symbRegProblem.FitnessCalculationPartition.Start = 0;
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| 296 | symbRegProblem.FitnessCalculationPartition.End = 2800;
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| 297 | symbRegProblem.ValidationPartition.Start = 2800;
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| 298 | symbRegProblem.ValidationPartition.End = 4000;
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[6474] | 299 | symbRegProblem.RelativeNumberOfEvaluatedSamples.Value = 1;
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[6441] | 300 | symbRegProblem.MaximumSymbolicExpressionTreeLength.Value = 150;
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| 301 | symbRegProblem.MaximumSymbolicExpressionTreeDepth.Value = 12;
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| 302 | symbRegProblem.MaximumFunctionDefinitions.Value = 0;
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| 303 | symbRegProblem.MaximumFunctionArguments.Value = 0;
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| 304 |
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| 305 | symbRegProblem.EvaluatorParameter.Value = new SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator();
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| 306 | #endregion
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[6544] | 307 | #region Algorithm Configuration
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[6441] | 308 | ga.Problem = symbRegProblem;
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| 309 | ga.Name = "Genetic Programming - Symbolic Regression";
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| 310 | ga.Description = "A standard genetic programming algorithm to solve a symbolic regression problem (tower dataset)";
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| 311 | ConfigureGeneticAlgorithmParameters<TournamentSelector, SubtreeCrossover, MultiSymbolicExpressionTreeManipulator>(
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[6474] | 312 | ga, 1000, 1, 50, 0.15, 5);
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[6441] | 313 | var mutator = (MultiSymbolicExpressionTreeManipulator)ga.Mutator;
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| 314 | mutator.Operators.OfType<FullTreeShaker>().Single().ShakingFactor = 0.1;
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| 315 | mutator.Operators.OfType<OnePointShaker>().Single().ShakingFactor = 1.0;
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| 316 |
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| 317 | ga.Analyzer.Operators.SetItemCheckedState(
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| 318 | ga.Analyzer.Operators
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| 319 | .OfType<SymbolicRegressionSingleObjectiveOverfittingAnalyzer>()
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| 320 | .Single(), false);
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[6474] | 321 | ga.Analyzer.Operators.SetItemCheckedState(
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| 322 | ga.Analyzer.Operators
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| 323 | .OfType<SymbolicDataAnalysisAlleleFrequencyAnalyzer>()
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| 324 | .First(), false);
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[6441] | 325 | #endregion
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[6468] | 326 | return ga;
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| 327 | }
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| 328 | #endregion
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[6544] | 329 | #region Symbolic Classification
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[6468] | 330 | [TestMethod]
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[6476] | 331 | public void CreateGpSymbolicClassificationSampleTest() {
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| 332 | var ga = CreateGpSymbolicClassificationSample();
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[6468] | 333 | XmlGenerator.Serialize(ga, "../../SGP_SymbClass.hl");
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| 334 | }
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[6441] | 335 |
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[6468] | 336 | [TestMethod]
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[6476] | 337 | public void RunGpSymbolicClassificationSampleTest() {
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| 338 | var ga = CreateGpSymbolicClassificationSample();
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[6468] | 339 | ga.SetSeedRandomly.Value = false;
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[6441] | 340 | RunAlgorithm(ga);
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[8335] | 341 | Assert.AreEqual(0.14458636369766503, GetDoubleResult(ga, "BestQuality"), 1E-8);
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| 342 | Assert.AreEqual(2.5613992769560352, GetDoubleResult(ga, "CurrentAverageQuality"), 1E-8);
|
---|
| 343 | Assert.AreEqual(100.62175156249987, GetDoubleResult(ga, "CurrentWorstQuality"), 1E-8);
|
---|
[6822] | 344 | Assert.AreEqual(100900, GetIntResult(ga, "EvaluatedSolutions"));
|
---|
[6441] | 345 | }
|
---|
| 346 |
|
---|
[6476] | 347 | private GeneticAlgorithm CreateGpSymbolicClassificationSample() {
|
---|
[6441] | 348 | GeneticAlgorithm ga = new GeneticAlgorithm();
|
---|
[6544] | 349 | #region Problem Configuration
|
---|
[6441] | 350 | SymbolicClassificationSingleObjectiveProblem symbClassProblem = new SymbolicClassificationSingleObjectiveProblem();
|
---|
| 351 | symbClassProblem.Name = "Mammography Classification Problem";
|
---|
| 352 | symbClassProblem.Description = "Mammography dataset imported from the UCI machine learning repository (http://archive.ics.uci.edu/ml/datasets/Mammographic+Mass)";
|
---|
[7849] | 353 | ClassificationRealWorldInstanceProvider provider = new ClassificationRealWorldInstanceProvider();
|
---|
[7863] | 354 | var instance = provider.GetDataDescriptors().Where(x => x.Name.Equals("Mammography")).Single();
|
---|
[7823] | 355 | var mammoData = (ClassificationProblemData)provider.LoadData(instance);
|
---|
[6441] | 356 | mammoData.TargetVariableParameter.Value = mammoData.TargetVariableParameter.ValidValues
|
---|
| 357 | .First(v => v.Value == "Severity");
|
---|
| 358 | mammoData.InputVariables.SetItemCheckedState(
|
---|
| 359 | mammoData.InputVariables.Single(x => x.Value == "BI-RADS"), false);
|
---|
| 360 | mammoData.InputVariables.SetItemCheckedState(
|
---|
| 361 | mammoData.InputVariables.Single(x => x.Value == "Age"), true);
|
---|
| 362 | mammoData.InputVariables.SetItemCheckedState(
|
---|
| 363 | mammoData.InputVariables.Single(x => x.Value == "Shape"), true);
|
---|
| 364 | mammoData.InputVariables.SetItemCheckedState(
|
---|
| 365 | mammoData.InputVariables.Single(x => x.Value == "Margin"), true);
|
---|
| 366 | mammoData.InputVariables.SetItemCheckedState(
|
---|
| 367 | mammoData.InputVariables.Single(x => x.Value == "Density"), true);
|
---|
| 368 | mammoData.InputVariables.SetItemCheckedState(
|
---|
| 369 | mammoData.InputVariables.Single(x => x.Value == "Severity"), false);
|
---|
| 370 | mammoData.TrainingPartition.Start = 0;
|
---|
| 371 | mammoData.TrainingPartition.End = 800;
|
---|
| 372 | mammoData.TestPartition.Start = 800;
|
---|
| 373 | mammoData.TestPartition.End = 961;
|
---|
| 374 | mammoData.Name = "Data imported from mammographic_masses.csv";
|
---|
| 375 | mammoData.Description = "Original dataset: http://archive.ics.uci.edu/ml/datasets/Mammographic+Mass, missing values have been replaced with median values.";
|
---|
| 376 | symbClassProblem.ProblemData = mammoData;
|
---|
| 377 |
|
---|
| 378 | // configure grammar
|
---|
| 379 | var grammar = new TypeCoherentExpressionGrammar();
|
---|
[6999] | 380 | grammar.ConfigureAsDefaultClassificationGrammar();
|
---|
| 381 | grammar.Symbols.OfType<VariableCondition>().Single().Enabled = false;
|
---|
[6441] | 382 | var varSymbol = grammar.Symbols.OfType<Variable>().Where(x => !(x is LaggedVariable)).Single();
|
---|
| 383 | varSymbol.WeightMu = 1.0;
|
---|
| 384 | varSymbol.WeightSigma = 1.0;
|
---|
| 385 | varSymbol.WeightManipulatorMu = 0.0;
|
---|
| 386 | varSymbol.WeightManipulatorSigma = 0.05;
|
---|
| 387 | varSymbol.MultiplicativeWeightManipulatorSigma = 0.03;
|
---|
| 388 | var constSymbol = grammar.Symbols.OfType<Constant>().Single();
|
---|
| 389 | constSymbol.MaxValue = 20;
|
---|
| 390 | constSymbol.MinValue = -20;
|
---|
| 391 | constSymbol.ManipulatorMu = 0.0;
|
---|
| 392 | constSymbol.ManipulatorSigma = 1;
|
---|
| 393 | constSymbol.MultiplicativeManipulatorSigma = 0.03;
|
---|
| 394 | symbClassProblem.SymbolicExpressionTreeGrammar = grammar;
|
---|
| 395 |
|
---|
| 396 | // configure remaining problem parameters
|
---|
| 397 | symbClassProblem.BestKnownQuality.Value = 0.0;
|
---|
| 398 | symbClassProblem.FitnessCalculationPartition.Start = 0;
|
---|
| 399 | symbClassProblem.FitnessCalculationPartition.End = 400;
|
---|
| 400 | symbClassProblem.ValidationPartition.Start = 400;
|
---|
| 401 | symbClassProblem.ValidationPartition.End = 800;
|
---|
| 402 | symbClassProblem.RelativeNumberOfEvaluatedSamples.Value = 1;
|
---|
| 403 | symbClassProblem.MaximumSymbolicExpressionTreeLength.Value = 100;
|
---|
| 404 | symbClassProblem.MaximumSymbolicExpressionTreeDepth.Value = 10;
|
---|
| 405 | symbClassProblem.MaximumFunctionDefinitions.Value = 0;
|
---|
| 406 | symbClassProblem.MaximumFunctionArguments.Value = 0;
|
---|
| 407 | symbClassProblem.EvaluatorParameter.Value = new SymbolicClassificationSingleObjectiveMeanSquaredErrorEvaluator();
|
---|
| 408 | #endregion
|
---|
[6544] | 409 | #region Algorithm Configuration
|
---|
[6441] | 410 | ga.Problem = symbClassProblem;
|
---|
| 411 | ga.Name = "Genetic Programming - Symbolic Classification";
|
---|
| 412 | ga.Description = "A standard genetic programming algorithm to solve a classification problem (Mammographic+Mass dataset)";
|
---|
| 413 | ConfigureGeneticAlgorithmParameters<TournamentSelector, SubtreeCrossover, MultiSymbolicExpressionTreeManipulator>(
|
---|
| 414 | ga, 1000, 1, 100, 0.15, 5
|
---|
| 415 | );
|
---|
| 416 |
|
---|
| 417 | var mutator = (MultiSymbolicExpressionTreeManipulator)ga.Mutator;
|
---|
| 418 | mutator.Operators.OfType<FullTreeShaker>().Single().ShakingFactor = 0.1;
|
---|
| 419 | mutator.Operators.OfType<OnePointShaker>().Single().ShakingFactor = 1.0;
|
---|
| 420 |
|
---|
| 421 | ga.Analyzer.Operators.SetItemCheckedState(
|
---|
| 422 | ga.Analyzer.Operators
|
---|
| 423 | .OfType<SymbolicClassificationSingleObjectiveOverfittingAnalyzer>()
|
---|
| 424 | .Single(), false);
|
---|
[6474] | 425 | ga.Analyzer.Operators.SetItemCheckedState(
|
---|
| 426 | ga.Analyzer.Operators
|
---|
| 427 | .OfType<SymbolicDataAnalysisAlleleFrequencyAnalyzer>()
|
---|
| 428 | .First(), false);
|
---|
[6441] | 429 | #endregion
|
---|
[6468] | 430 | return ga;
|
---|
[6441] | 431 | }
|
---|
[6468] | 432 | #endregion
|
---|
[8132] | 433 | #region LawnMower
|
---|
| 434 | [TestMethod]
|
---|
| 435 | public void RunGpLawnMowerSampleTest() {
|
---|
| 436 | var ga = CreateGpLawnMowerSample();
|
---|
| 437 | ga.SetSeedRandomly.Value = false;
|
---|
| 438 | RunAlgorithm(ga);
|
---|
| 439 | }
|
---|
| 440 |
|
---|
| 441 | public GeneticAlgorithm CreateGpLawnMowerSample() {
|
---|
| 442 | GeneticAlgorithm ga = new GeneticAlgorithm();
|
---|
| 443 | #region Problem Configuration
|
---|
| 444 | var problem = new HeuristicLab.Problems.LawnMower.Problem();
|
---|
| 445 | #endregion
|
---|
| 446 | #region Algorithm Configuration
|
---|
| 447 | ga.Name = "Genetic Programming - Lawn Mower";
|
---|
| 448 | ga.Description = "A standard genetic programming algorithm to solve the lawn mower problem";
|
---|
| 449 | ga.Problem = problem;
|
---|
| 450 | ConfigureGeneticAlgorithmParameters<TournamentSelector, SubtreeCrossover, MultiSymbolicExpressionTreeArchitectureManipulator>(
|
---|
| 451 | ga, 1000, 1, 50, 0.25, 5);
|
---|
| 452 | var mutator = (MultiSymbolicExpressionTreeArchitectureManipulator)ga.Mutator;
|
---|
| 453 | mutator.Operators.SetItemCheckedState(mutator.Operators
|
---|
| 454 | .OfType<OnePointShaker>()
|
---|
| 455 | .Single(), false);
|
---|
| 456 | #endregion
|
---|
| 457 | return ga;
|
---|
| 458 | }
|
---|
[6476] | 459 | #endregion
|
---|
[8132] | 460 | #endregion
|
---|
[6441] | 461 |
|
---|
[6476] | 462 | #region ES
|
---|
| 463 | #region Griewank
|
---|
| 464 | [TestMethod]
|
---|
| 465 | public void CreateEsGriewankSampleTest() {
|
---|
| 466 | var es = CreateEsGriewankSample();
|
---|
| 467 | XmlGenerator.Serialize(es, "../../ES_Griewank.hl");
|
---|
| 468 | }
|
---|
| 469 | [TestMethod]
|
---|
| 470 | public void RunEsGriewankSampleTest() {
|
---|
| 471 | var es = CreateEsGriewankSample();
|
---|
| 472 | es.SetSeedRandomly.Value = false;
|
---|
| 473 | RunAlgorithm(es);
|
---|
| 474 | Assert.AreEqual(0, GetDoubleResult(es, "BestQuality"));
|
---|
| 475 | Assert.AreEqual(0, GetDoubleResult(es, "CurrentAverageQuality"));
|
---|
| 476 | Assert.AreEqual(0, GetDoubleResult(es, "CurrentWorstQuality"));
|
---|
| 477 | Assert.AreEqual(100020, GetIntResult(es, "EvaluatedSolutions"));
|
---|
| 478 | }
|
---|
| 479 |
|
---|
| 480 | private EvolutionStrategy CreateEsGriewankSample() {
|
---|
| 481 | EvolutionStrategy es = new EvolutionStrategy();
|
---|
[6544] | 482 | #region Problem Configuration
|
---|
[6476] | 483 | SingleObjectiveTestFunctionProblem problem = new SingleObjectiveTestFunctionProblem();
|
---|
| 484 |
|
---|
| 485 | problem.ProblemSize.Value = 10;
|
---|
[6938] | 486 | problem.EvaluatorParameter.Value = new GriewankEvaluator();
|
---|
| 487 | problem.SolutionCreatorParameter.Value = new UniformRandomRealVectorCreator();
|
---|
[6476] | 488 | problem.Maximization.Value = false;
|
---|
| 489 | problem.Bounds = new DoubleMatrix(new double[,] { { -600, 600 } });
|
---|
| 490 | problem.BestKnownQuality.Value = 0;
|
---|
| 491 | problem.BestKnownSolutionParameter.Value = new RealVector(10);
|
---|
| 492 | problem.Name = "Single Objective Test Function";
|
---|
| 493 | problem.Description = "Test function with real valued inputs and a single objective.";
|
---|
| 494 | #endregion
|
---|
[6544] | 495 | #region Algorithm Configuration
|
---|
[6476] | 496 | es.Name = "Evolution Strategy - Griewank";
|
---|
| 497 | es.Description = "An evolution strategy which solves the 10-dimensional Griewank test function";
|
---|
| 498 | es.Problem = problem;
|
---|
| 499 | ConfigureEvolutionStrategyParameters<AverageCrossover, NormalAllPositionsManipulator,
|
---|
| 500 | StdDevStrategyVectorCreator, StdDevStrategyVectorCrossover, StdDevStrategyVectorManipulator>(
|
---|
| 501 | es, 20, 500, 2, 200, false);
|
---|
| 502 |
|
---|
| 503 | StdDevStrategyVectorCreator strategyCreator = (StdDevStrategyVectorCreator)es.StrategyParameterCreator;
|
---|
| 504 | strategyCreator.BoundsParameter.Value = new DoubleMatrix(new double[,] { { 1, 20 } });
|
---|
| 505 |
|
---|
| 506 | StdDevStrategyVectorManipulator strategyManipulator = (StdDevStrategyVectorManipulator)es.StrategyParameterManipulator;
|
---|
| 507 | strategyManipulator.BoundsParameter.Value = new DoubleMatrix(new double[,] { { 1E-12, 30 } });
|
---|
| 508 | strategyManipulator.GeneralLearningRateParameter.Value = new DoubleValue(0.22360679774997896);
|
---|
| 509 | strategyManipulator.LearningRateParameter.Value = new DoubleValue(0.39763536438352531);
|
---|
| 510 | #endregion
|
---|
| 511 | return es;
|
---|
| 512 | }
|
---|
| 513 | #endregion
|
---|
| 514 | #endregion
|
---|
| 515 |
|
---|
| 516 | #region Island GA
|
---|
| 517 | #region TSP
|
---|
| 518 | [TestMethod]
|
---|
| 519 | public void CreateIslandGaTspSampleTest() {
|
---|
| 520 | var ga = CreateIslandGaTspSample();
|
---|
| 521 | XmlGenerator.Serialize(ga, "../../IslandGA_TSP.hl");
|
---|
| 522 | }
|
---|
| 523 | [TestMethod]
|
---|
| 524 | public void RunIslandGaTspSampleTest() {
|
---|
| 525 | var ga = CreateIslandGaTspSample();
|
---|
| 526 | ga.SetSeedRandomly.Value = false;
|
---|
| 527 | RunAlgorithm(ga);
|
---|
[7397] | 528 | Assert.AreEqual(9918, GetDoubleResult(ga, "BestQuality"));
|
---|
| 529 | Assert.AreEqual(10324.64, GetDoubleResult(ga, "CurrentAverageQuality"));
|
---|
| 530 | Assert.AreEqual(11823, GetDoubleResult(ga, "CurrentWorstQuality"));
|
---|
[6476] | 531 | Assert.AreEqual(495500, GetIntResult(ga, "EvaluatedSolutions"));
|
---|
| 532 | }
|
---|
| 533 |
|
---|
| 534 | private IslandGeneticAlgorithm CreateIslandGaTspSample() {
|
---|
| 535 | IslandGeneticAlgorithm ga = new IslandGeneticAlgorithm();
|
---|
[6544] | 536 | #region Problem Configuration
|
---|
[7558] | 537 | var provider = new TSPLIBTSPInstanceProvider();
|
---|
| 538 | var instance = provider.GetDataDescriptors().Where(x => x.Name == "ch130").Single();
|
---|
[6476] | 539 | TravelingSalesmanProblem tspProblem = new TravelingSalesmanProblem();
|
---|
[7558] | 540 | tspProblem.Load(provider.LoadData(instance));
|
---|
[6476] | 541 | tspProblem.UseDistanceMatrix.Value = true;
|
---|
| 542 | #endregion
|
---|
[6544] | 543 | #region Algorithm Configuration
|
---|
[6476] | 544 | ga.Name = "Island Genetic Algorithm - TSP";
|
---|
| 545 | ga.Description = "An island genetic algorithm which solves the \"ch130\" traveling salesman problem (imported from TSPLIB)";
|
---|
| 546 | ga.Problem = tspProblem;
|
---|
| 547 | ConfigureIslandGeneticAlgorithmParameters<ProportionalSelector, OrderCrossover2, InversionManipulator,
|
---|
| 548 | UnidirectionalRingMigrator, BestSelector, WorstReplacer>(
|
---|
| 549 | ga, 100, 1, 1000, 0.05, 5, 50, 0.25);
|
---|
| 550 | #endregion
|
---|
| 551 | return ga;
|
---|
| 552 | }
|
---|
| 553 | #endregion
|
---|
| 554 | #endregion
|
---|
| 555 |
|
---|
| 556 | #region LS
|
---|
| 557 | #region Knapsack
|
---|
| 558 | [TestMethod]
|
---|
| 559 | public void CreateLocalSearchKnapsackSampleTest() {
|
---|
| 560 | var ls = CreateLocalSearchKnapsackSample();
|
---|
| 561 | XmlGenerator.Serialize(ls, "../../LS_Knapsack.hl");
|
---|
| 562 | }
|
---|
| 563 | [TestMethod]
|
---|
| 564 | public void RunLocalSearchKnapsackSampleTest() {
|
---|
| 565 | var ls = CreateLocalSearchKnapsackSample();
|
---|
| 566 | ls.SetSeedRandomly.Value = false;
|
---|
| 567 | RunAlgorithm(ls);
|
---|
| 568 | Assert.AreEqual(345, GetDoubleResult(ls, "BestQuality"));
|
---|
| 569 | Assert.AreEqual(340.70731707317071, GetDoubleResult(ls, "CurrentAverageQuality"));
|
---|
| 570 | Assert.AreEqual(337, GetDoubleResult(ls, "CurrentWorstQuality"));
|
---|
| 571 | Assert.AreEqual(82000, GetIntResult(ls, "EvaluatedMoves"));
|
---|
| 572 | }
|
---|
| 573 |
|
---|
| 574 | private LocalSearch CreateLocalSearchKnapsackSample() {
|
---|
| 575 | LocalSearch ls = new LocalSearch();
|
---|
[6544] | 576 | #region Problem Configuration
|
---|
[6476] | 577 | KnapsackProblem problem = new KnapsackProblem();
|
---|
[7442] | 578 | problem.BestKnownQuality = new DoubleValue(362);
|
---|
[6476] | 579 | problem.BestKnownSolution = new HeuristicLab.Encodings.BinaryVectorEncoding.BinaryVector(new bool[] {
|
---|
| 580 | 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});
|
---|
[6938] | 581 | problem.EvaluatorParameter.Value = new KnapsackEvaluator();
|
---|
| 582 | problem.SolutionCreatorParameter.Value = new RandomBinaryVectorCreator();
|
---|
[6476] | 583 | problem.KnapsackCapacity.Value = 297;
|
---|
| 584 | problem.Maximization.Value = true;
|
---|
| 585 | problem.Penalty.Value = 1;
|
---|
| 586 | problem.Values = new IntArray(new int[] {
|
---|
| 587 | 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});
|
---|
| 588 | problem.Weights = new IntArray(new int[] {
|
---|
| 589 | 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});
|
---|
| 590 | problem.Name = "Knapsack Problem";
|
---|
| 591 | problem.Description = "Represents a Knapsack problem.";
|
---|
| 592 | #endregion
|
---|
[6544] | 593 | #region Algorithm Configuration
|
---|
[6476] | 594 | ls.Name = "Local Search - Knapsack";
|
---|
| 595 | ls.Description = "A local search algorithm that solves a randomly generated Knapsack problem";
|
---|
| 596 | ls.Problem = problem;
|
---|
| 597 | ls.MaximumIterations.Value = 1000;
|
---|
| 598 | ls.MoveEvaluator = ls.MoveEvaluatorParameter.ValidValues
|
---|
| 599 | .OfType<KnapsackOneBitflipMoveEvaluator>()
|
---|
| 600 | .Single();
|
---|
| 601 | ls.MoveGenerator = ls.MoveGeneratorParameter.ValidValues
|
---|
| 602 | .OfType<ExhaustiveOneBitflipMoveGenerator>()
|
---|
| 603 | .Single();
|
---|
| 604 | ls.MoveMaker = ls.MoveMakerParameter.ValidValues
|
---|
| 605 | .OfType<OneBitflipMoveMaker>()
|
---|
| 606 | .Single();
|
---|
| 607 | ls.SampleSize.Value = 100;
|
---|
| 608 | ls.Seed.Value = 0;
|
---|
| 609 | ls.SetSeedRandomly.Value = true;
|
---|
| 610 | #endregion
|
---|
| 611 | ls.Engine = new ParallelEngine();
|
---|
| 612 | return ls;
|
---|
| 613 | }
|
---|
| 614 | #endregion
|
---|
| 615 | #endregion
|
---|
| 616 |
|
---|
| 617 | #region PSO
|
---|
| 618 | #region Schwefel
|
---|
| 619 | [TestMethod]
|
---|
| 620 | public void CreatePsoSchwefelSampleTest() {
|
---|
| 621 | var pso = CreatePsoSchwefelSample();
|
---|
| 622 | XmlGenerator.Serialize(pso, "../../PSO_Schwefel.hl");
|
---|
| 623 | }
|
---|
| 624 | [TestMethod]
|
---|
| 625 | public void RunPsoSchwefelSampleTest() {
|
---|
| 626 | var pso = CreatePsoSchwefelSample();
|
---|
| 627 | pso.SetSeedRandomly.Value = false;
|
---|
| 628 | RunAlgorithm(pso);
|
---|
[6505] | 629 | if (!Environment.Is64BitProcess) {
|
---|
[7082] | 630 | Assert.AreEqual(118.44027985932837, GetDoubleResult(pso, "BestQuality"));
|
---|
[6505] | 631 | Assert.AreEqual(140.71570105946438, GetDoubleResult(pso, "CurrentAverageQuality"));
|
---|
| 632 | Assert.AreEqual(220.956806502853, GetDoubleResult(pso, "CurrentWorstQuality"));
|
---|
| 633 | Assert.AreEqual(1000, GetIntResult(pso, "Iterations"));
|
---|
| 634 | } else {
|
---|
[7082] | 635 | Assert.AreEqual(118.43958282879345, GetDoubleResult(pso, "BestQuality"));
|
---|
[6505] | 636 | Assert.AreEqual(139.43946864779372, GetDoubleResult(pso, "CurrentAverageQuality"));
|
---|
| 637 | Assert.AreEqual(217.14654589055152, GetDoubleResult(pso, "CurrentWorstQuality"));
|
---|
| 638 | Assert.AreEqual(1000, GetIntResult(pso, "Iterations"));
|
---|
| 639 | }
|
---|
[6476] | 640 | }
|
---|
| 641 | private ParticleSwarmOptimization CreatePsoSchwefelSample() {
|
---|
| 642 | ParticleSwarmOptimization pso = new ParticleSwarmOptimization();
|
---|
[6544] | 643 | #region Problem Configuration
|
---|
[6476] | 644 | var problem = new SingleObjectiveTestFunctionProblem();
|
---|
| 645 | problem.BestKnownQuality.Value = 0.0;
|
---|
| 646 | problem.BestKnownSolutionParameter.Value = new RealVector(new double[] { 420.968746, 420.968746 });
|
---|
| 647 | problem.Bounds = new DoubleMatrix(new double[,] { { -500, 500 } });
|
---|
[6938] | 648 | problem.EvaluatorParameter.Value = new SchwefelEvaluator();
|
---|
[6476] | 649 | problem.Maximization.Value = false;
|
---|
| 650 | problem.ProblemSize.Value = 2;
|
---|
[6938] | 651 | problem.SolutionCreatorParameter.Value = new UniformRandomRealVectorCreator();
|
---|
[6476] | 652 | #endregion
|
---|
[6544] | 653 | #region Algorithm Configuration
|
---|
[6476] | 654 | pso.Name = "Particle Swarm Optimization - Schwefel";
|
---|
| 655 | pso.Description = "A particle swarm optimization algorithm which solves the 2-dimensional Schwefel test function (based on the description in Pedersen, M.E.H. (2010). PhD thesis. University of Southampton)";
|
---|
| 656 | pso.Problem = problem;
|
---|
| 657 | pso.Inertia.Value = 10;
|
---|
| 658 | pso.MaxIterations.Value = 1000;
|
---|
| 659 | pso.NeighborBestAttraction.Value = 0.5;
|
---|
| 660 | pso.PersonalBestAttraction.Value = -0.01;
|
---|
| 661 | pso.SwarmSize.Value = 50;
|
---|
| 662 |
|
---|
| 663 | var inertiaUpdater = pso.InertiaUpdaterParameter.ValidValues
|
---|
| 664 | .OfType<ExponentialDiscreteDoubleValueModifier>()
|
---|
| 665 | .Single();
|
---|
| 666 | inertiaUpdater.StartValueParameter.Value = new DoubleValue(10);
|
---|
| 667 | inertiaUpdater.EndValueParameter.Value = new DoubleValue(1);
|
---|
| 668 | pso.InertiaUpdater = inertiaUpdater;
|
---|
| 669 |
|
---|
| 670 | pso.ParticleCreator = pso.ParticleCreatorParameter.ValidValues
|
---|
| 671 | .OfType<RealVectorParticleCreator>()
|
---|
| 672 | .Single();
|
---|
| 673 | var swarmUpdater = pso.SwarmUpdaterParameter.ValidValues
|
---|
| 674 | .OfType<RealVectorSwarmUpdater>()
|
---|
| 675 | .Single();
|
---|
| 676 | swarmUpdater.VelocityBoundsIndexParameter.ActualName = "Iterations";
|
---|
| 677 | swarmUpdater.VelocityBoundsParameter.Value = new DoubleMatrix(new double[,] { { -10, 10 } });
|
---|
| 678 | swarmUpdater.VelocityBoundsStartValueParameter.Value = new DoubleValue(10.0);
|
---|
| 679 | swarmUpdater.VelocityBoundsEndValueParameter.Value = new DoubleValue(1.0);
|
---|
| 680 | swarmUpdater.VelocityBoundsScalingOperatorParameter.Value = swarmUpdater.VelocityBoundsScalingOperatorParameter.ValidValues
|
---|
| 681 | .OfType<ExponentialDiscreteDoubleValueModifier>()
|
---|
| 682 | .Single();
|
---|
| 683 |
|
---|
| 684 | pso.TopologyInitializer = null;
|
---|
| 685 | pso.TopologyUpdater = null;
|
---|
| 686 | pso.SwarmUpdater = swarmUpdater;
|
---|
| 687 | pso.Seed.Value = 0;
|
---|
| 688 | pso.SetSeedRandomly.Value = true;
|
---|
| 689 | #endregion
|
---|
| 690 | pso.Engine = new ParallelEngine();
|
---|
| 691 | return pso;
|
---|
| 692 | }
|
---|
| 693 | #endregion
|
---|
| 694 | #endregion
|
---|
| 695 |
|
---|
| 696 | #region SA
|
---|
| 697 | #region Rastrigin
|
---|
| 698 | [TestMethod]
|
---|
| 699 | public void CreateSimulatedAnnealingRastriginSampleTest() {
|
---|
| 700 | var sa = CreateSimulatedAnnealingRastriginSample();
|
---|
| 701 | XmlGenerator.Serialize(sa, "../../SA_Rastrigin.hl");
|
---|
| 702 | }
|
---|
| 703 | [TestMethod]
|
---|
| 704 | public void RunSimulatedAnnealingRastriginSampleTest() {
|
---|
| 705 | var sa = CreateSimulatedAnnealingRastriginSample();
|
---|
| 706 | sa.SetSeedRandomly.Value = false;
|
---|
| 707 | RunAlgorithm(sa);
|
---|
| 708 | Assert.AreEqual(0.00014039606034543795, GetDoubleResult(sa, "BestQuality"));
|
---|
| 709 | Assert.AreEqual(5000, GetIntResult(sa, "EvaluatedMoves"));
|
---|
| 710 | }
|
---|
| 711 | private SimulatedAnnealing CreateSimulatedAnnealingRastriginSample() {
|
---|
| 712 | SimulatedAnnealing sa = new SimulatedAnnealing();
|
---|
[6544] | 713 | #region Problem Configuration
|
---|
[6476] | 714 | var problem = new SingleObjectiveTestFunctionProblem();
|
---|
| 715 | problem.BestKnownQuality.Value = 0.0;
|
---|
| 716 | problem.BestKnownSolutionParameter.Value = new RealVector(new double[] { 0, 0 });
|
---|
| 717 | problem.Bounds = new DoubleMatrix(new double[,] { { -5.12, 5.12 } });
|
---|
[6938] | 718 | problem.EvaluatorParameter.Value = new RastriginEvaluator();
|
---|
[6476] | 719 | problem.Maximization.Value = false;
|
---|
| 720 | problem.ProblemSize.Value = 2;
|
---|
[6938] | 721 | problem.SolutionCreatorParameter.Value = new UniformRandomRealVectorCreator();
|
---|
[6476] | 722 | #endregion
|
---|
[6544] | 723 | #region Algorithm Configuration
|
---|
[6476] | 724 | sa.Name = "Simulated Annealing - Rastrigin";
|
---|
| 725 | sa.Description = "A simulated annealing algorithm that solves the 2-dimensional Rastrigin test function";
|
---|
| 726 | sa.Problem = problem;
|
---|
| 727 | var annealingOperator = sa.AnnealingOperatorParameter.ValidValues
|
---|
| 728 | .OfType<ExponentialDiscreteDoubleValueModifier>()
|
---|
| 729 | .Single();
|
---|
| 730 | annealingOperator.StartIndexParameter.Value = new IntValue(0);
|
---|
| 731 | sa.AnnealingOperator = annealingOperator;
|
---|
| 732 |
|
---|
| 733 | sa.EndTemperature.Value = 1E-6;
|
---|
| 734 | sa.InnerIterations.Value = 50;
|
---|
| 735 | sa.MaximumIterations.Value = 100;
|
---|
| 736 | var moveEvaluator = sa.MoveEvaluatorParameter.ValidValues
|
---|
| 737 | .OfType<RastriginAdditiveMoveEvaluator>()
|
---|
| 738 | .Single();
|
---|
| 739 | moveEvaluator.A.Value = 10;
|
---|
| 740 | sa.MoveEvaluator = moveEvaluator;
|
---|
| 741 |
|
---|
| 742 | var moveGenerator = sa.MoveGeneratorParameter.ValidValues
|
---|
| 743 | .OfType<StochasticNormalMultiMoveGenerator>()
|
---|
| 744 | .Single();
|
---|
| 745 | moveGenerator.SigmaParameter.Value = new DoubleValue(1);
|
---|
| 746 | sa.MoveGenerator = moveGenerator;
|
---|
| 747 |
|
---|
| 748 | sa.MoveMaker = sa.MoveMakerParameter.ValidValues
|
---|
| 749 | .OfType<AdditiveMoveMaker>()
|
---|
| 750 | .Single();
|
---|
| 751 |
|
---|
| 752 | sa.Seed.Value = 0;
|
---|
| 753 | sa.SetSeedRandomly.Value = true;
|
---|
| 754 | sa.StartTemperature.Value = 1;
|
---|
| 755 | #endregion
|
---|
| 756 | sa.Engine = new ParallelEngine();
|
---|
| 757 | return sa;
|
---|
| 758 | }
|
---|
| 759 | #endregion
|
---|
| 760 | #endregion
|
---|
| 761 |
|
---|
| 762 | #region TS
|
---|
| 763 | #region TSP
|
---|
| 764 | [TestMethod]
|
---|
| 765 | public void CreateTabuSearchTspSampleTest() {
|
---|
| 766 | var ts = CreateTabuSearchTspSample();
|
---|
| 767 | XmlGenerator.Serialize(ts, "../../TS_TSP.hl");
|
---|
| 768 | }
|
---|
| 769 | [TestMethod]
|
---|
| 770 | public void RunTabuSearchTspSampleTest() {
|
---|
| 771 | var ts = CreateTabuSearchTspSample();
|
---|
| 772 | ts.SetSeedRandomly.Value = false;
|
---|
| 773 | RunAlgorithm(ts);
|
---|
| 774 | Assert.AreEqual(6441, GetDoubleResult(ts, "BestQuality"));
|
---|
| 775 | Assert.AreEqual(7401.666666666667, GetDoubleResult(ts, "CurrentAverageQuality"));
|
---|
| 776 | Assert.AreEqual(8418, GetDoubleResult(ts, "CurrentWorstQuality"));
|
---|
| 777 | Assert.AreEqual(750000, GetIntResult(ts, "EvaluatedMoves"));
|
---|
| 778 | }
|
---|
| 779 |
|
---|
| 780 | private TabuSearch CreateTabuSearchTspSample() {
|
---|
| 781 | TabuSearch ts = new TabuSearch();
|
---|
[6544] | 782 | #region Problem Configuration
|
---|
[7558] | 783 | var provider = new TSPLIBTSPInstanceProvider();
|
---|
| 784 | var instance = provider.GetDataDescriptors().Where(x => x.Name == "ch130").Single();
|
---|
| 785 | TravelingSalesmanProblem tspProblem = new TravelingSalesmanProblem();
|
---|
| 786 | tspProblem.Load(provider.LoadData(instance));
|
---|
[6476] | 787 | tspProblem.UseDistanceMatrix.Value = true;
|
---|
| 788 | #endregion
|
---|
[6544] | 789 | #region Algorithm Configuration
|
---|
[6476] | 790 | ts.Name = "Tabu Search - TSP";
|
---|
| 791 | ts.Description = "A tabu search algorithm that solves the \"ch130\" TSP (imported from TSPLIB)";
|
---|
| 792 | ts.Problem = tspProblem;
|
---|
| 793 |
|
---|
| 794 | ts.MaximumIterations.Value = 1000;
|
---|
| 795 | // move generator has to be set first
|
---|
| 796 | var moveGenerator = ts.MoveGeneratorParameter.ValidValues
|
---|
| 797 | .OfType<StochasticInversionMultiMoveGenerator>()
|
---|
| 798 | .Single();
|
---|
| 799 | ts.MoveGenerator = moveGenerator;
|
---|
| 800 | var moveEvaluator = ts.MoveEvaluatorParameter.ValidValues
|
---|
| 801 | .OfType<TSPInversionMoveRoundedEuclideanPathEvaluator>()
|
---|
| 802 | .Single();
|
---|
| 803 | ts.MoveEvaluator = moveEvaluator;
|
---|
| 804 | var moveMaker = ts.MoveMakerParameter.ValidValues
|
---|
| 805 | .OfType<InversionMoveMaker>()
|
---|
| 806 | .Single();
|
---|
| 807 | ts.MoveMaker = moveMaker;
|
---|
| 808 | ts.SampleSize.Value = 750;
|
---|
| 809 | ts.Seed.Value = 0;
|
---|
| 810 | ts.SetSeedRandomly.Value = true;
|
---|
| 811 |
|
---|
| 812 | var tabuChecker = ts.TabuCheckerParameter.ValidValues
|
---|
| 813 | .OfType<InversionMoveSoftTabuCriterion>()
|
---|
| 814 | .Single();
|
---|
| 815 | tabuChecker.UseAspirationCriterion.Value = true;
|
---|
| 816 | ts.TabuChecker = tabuChecker;
|
---|
| 817 |
|
---|
| 818 | var tabuMaker = ts.TabuMakerParameter.ValidValues
|
---|
| 819 | .OfType<InversionMoveTabuMaker>()
|
---|
| 820 | .Single();
|
---|
| 821 | ts.TabuMaker = tabuMaker;
|
---|
| 822 | ts.TabuTenure.Value = 60;
|
---|
| 823 |
|
---|
| 824 | #endregion
|
---|
| 825 | ts.Engine = new ParallelEngine();
|
---|
| 826 | return ts;
|
---|
| 827 | }
|
---|
| 828 | #endregion
|
---|
| 829 | #endregion
|
---|
| 830 |
|
---|
| 831 | #region VNS
|
---|
| 832 | #region TSP
|
---|
| 833 | [TestMethod]
|
---|
| 834 | public void CreateVnsTspSampleTest() {
|
---|
| 835 | var vns = CreateVnsTspSample();
|
---|
| 836 | XmlGenerator.Serialize(vns, "../../VNS_TSP.hl");
|
---|
| 837 | }
|
---|
| 838 | [TestMethod]
|
---|
| 839 | public void RunVnsTspSampleTest() {
|
---|
| 840 | var vns = CreateVnsTspSample();
|
---|
| 841 | vns.SetSeedRandomly = false;
|
---|
| 842 | RunAlgorithm(vns);
|
---|
| 843 | Assert.AreEqual(867, GetDoubleResult(vns, "BestQuality"));
|
---|
| 844 | Assert.AreEqual(867, GetDoubleResult(vns, "CurrentAverageQuality"));
|
---|
| 845 | Assert.AreEqual(867, GetDoubleResult(vns, "CurrentWorstQuality"));
|
---|
[6477] | 846 | Assert.AreEqual(12975173, GetIntResult(vns, "EvaluatedSolutions"));
|
---|
[6476] | 847 | }
|
---|
| 848 |
|
---|
| 849 | private VariableNeighborhoodSearch CreateVnsTspSample() {
|
---|
| 850 | VariableNeighborhoodSearch vns = new VariableNeighborhoodSearch();
|
---|
[6544] | 851 | #region Problem Configuration
|
---|
[6476] | 852 | TravelingSalesmanProblem tspProblem = new TravelingSalesmanProblem();
|
---|
| 853 | tspProblem.BestKnownSolution = new Permutation(PermutationTypes.Absolute, new int[] {
|
---|
| 854 | 117, 65, 73, 74, 75, 76, 82, 86, 87, 94, 100, 106, 115, 120, 124, 107, 101, 108, 109, 102, 97, 90, 96, 95, 88, 89, 84, 78, 69, 57, 68, 56, 44, 55, 45, 36, 46, 37, 38, 47, 48, 59, 49, 58, 70, 77, 83, 79, 50, 80, 85, 98, 103, 110, 116, 121, 125, 133, 132, 138, 139, 146, 147, 159, 168, 169, 175, 182, 188, 201, 213, 189, 214, 221, 230, 246, 262, 276, 284, 275, 274, 261, 245, 229, 220, 228, 243, 259, 273, 282, 272, 258, 242, 257, 293, 292, 302, 310, 319, 320, 327, 326, 333, 340, 346, 339, 345, 344, 337, 338, 332, 325, 318, 309, 301, 291, 271, 251, 270, 233, 250, 269, 268, 280, 290, 300, 415, 440, 416, 417, 441, 458, 479, 418, 419, 395, 420, 442, 421, 396, 397, 422, 423, 461, 481, 502, 460, 501, 459, 480, 500, 517, 531, 516, 530, 499, 478, 457, 439, 414, 413, 412, 438, 456, 477, 498, 515, 529, 538, 547, 558, 559, 560, 548, 539, 549, 561, 562, 551, 550, 532, 540, 533, 541, 518, 534, 542, 552, 553, 554, 555, 535, 543, 556, 544, 536, 522, 505, 521, 520, 504, 519, 503, 482, 462, 463, 464, 483, 443, 465, 484, 506, 485, 507, 508, 487, 467, 486, 466, 445, 428, 444, 424, 425, 426, 427, 398, 399, 400, 381, 382, 371, 372, 401, 429, 446, 430, 402, 383, 366, 356, 357, 352, 385, 384, 403, 431, 447, 469, 468, 488, 489, 490, 470, 471, 448, 432, 433, 404, 405, 386, 373, 374, 367, 376, 375, 387, 491, 509, 537, 510, 492, 472, 449, 388, 389, 406, 450, 407, 377, 368, 359, 354, 350, 335, 324, 330, 390, 434, 451, 473, 493, 511, 523, 545, 563, 565, 567, 570, 569, 578, 577, 576, 575, 574, 573, 572, 580, 584, 583, 582, 587, 586, 585, 581, 579, 571, 568, 566, 564, 557, 546, 527, 513, 526, 525, 524, 512, 495, 494, 474, 452, 436, 409, 435, 453, 475, 496, 514, 528, 497, 455, 476, 454, 437, 411, 410, 394, 393, 392, 380, 370, 379, 408, 391, 378, 369, 364, 365, 361, 355, 351, 343, 336, 331, 317, 299, 286, 287, 278, 263, 264, 265, 223, 202, 248, 266, 279, 288, 289, 281, 267, 249, 232, 224, 216, 215, 204, 192, 193, 194, 186, 179, 185, 203, 191, 190, 177, 171, 161, 128, 135, 140, 149, 162, 150, 163, 172, 178, 173, 164, 152, 151, 141, 153, 165, 154, 142, 155, 143, 137, 136, 130, 129, 118, 114, 113, 105, 119, 123, 131, 144, 156, 157, 145, 158, 166, 167, 174, 180, 181, 187, 195, 205, 217, 226, 236, 225, 234, 252, 235, 253, 254, 255, 238, 239, 240, 241, 256, 237, 206, 207, 208, 196, 197, 198, 209, 199, 200, 211, 212, 219, 210, 218, 227, 244, 260, 283, 294, 295, 303, 296, 311, 304, 297, 298, 305, 285, 306, 314, 329, 321, 313, 312, 328, 334, 341, 347, 348, 353, 358, 362, 363, 360, 349, 342, 322, 323, 315, 316, 308, 307, 277, 247, 231, 222, 184, 183, 176, 170, 160, 148, 134, 127, 126, 111, 104, 92, 91, 71, 60, 51, 52, 40, 32, 23, 21, 20, 18, 17, 16, 14, 13, 11, 10, 7, 6, 5, 2, 1, 0, 3, 4, 31, 39, 25, 30, 35, 34, 33, 43, 54, 42, 27, 28, 29, 9, 8, 12, 15, 19, 22, 24, 26, 41, 67, 66, 64, 63, 53, 62, 61, 72, 81, 93, 99, 112, 122,
|
---|
| 855 | });
|
---|
| 856 | tspProblem.Coordinates = new DoubleMatrix(new double[,] {
|
---|
| 857 | {48, 71}, {49, 71}, {50, 71}, {44, 70}, {45, 70}, {52, 70}, {53, 70}, {54, 70}, {41, 69}, {42, 69}, {55, 69}, {56, 69}, {40, 68}, {56, 68}, {57, 68}, {39, 67}, {57, 67}, {58, 67}, {59, 67}, {38, 66}, {59, 66}, {60, 66}, {37, 65}, {60, 65}, {36, 64}, {43, 64}, {35, 63}, {37, 63}, {41, 63}, {42, 63}, {43, 63}, {47, 63}, {61, 63}, {40, 62}, {41, 62}, {42, 62}, {43, 62}, {45, 62}, {46, 62}, {47, 62}, {62, 62}, {34, 61}, {38, 61}, {39, 61}, {42, 61}, {43, 61}, {44, 61}, {45, 61}, {46, 61}, {47, 61}, {52, 61}, {62, 61}, {63, 61}, {26, 60}, {38, 60}, {42, 60}, {43, 60}, {44, 60}, {46, 60}, {47, 60}, {63, 60}, {23, 59}, {24, 59}, {27, 59}, {29, 59}, {30, 59}, {31, 59}, {33, 59}, {42, 59}, {46, 59}, {47, 59}, {63, 59}, {21, 58}, {32, 58}, {33, 58}, {34, 58}, {35, 58}, {46, 58}, {47, 58}, {48, 58}, {53, 58}, {21, 57}, {35, 57}, {47, 57}, {48, 57}, {53, 57}, {36, 56}, {37, 56}, {46, 56}, {47, 56}, {48, 56}, {64, 56}, {65, 56}, {20, 55}, {38, 55}, {46, 55}, {47, 55}, {48, 55}, {52, 55}, {21, 54}, {40, 54}, {47, 54}, {48, 54}, {52, 54}, {65, 54}, {30, 53}, {41, 53}, {46, 53}, {47, 53}, {48, 53}, {52, 53}, {65, 53}, {21, 52}, {32, 52}, {33, 52}, {42, 52}, {51, 52}, {21, 51}, {33, 51}, {34, 51}, {43, 51}, {51, 51}, {21, 50}, {35, 50}, {44, 50}, {50, 50}, {66, 50}, {67, 50}, {21, 49}, {34, 49}, {36, 49}, {37, 49}, {46, 49}, {49, 49}, {67, 49}, {22, 48}, {36, 48}, {37, 48}, {46, 48}, {47, 48}, {22, 47}, {30, 47}, {34, 47}, {37, 47}, {38, 47}, {39, 47}, {47, 47}, {48, 47}, {67, 47}, {23, 46}, {28, 46}, {29, 46}, {30, 46}, {31, 46}, {32, 46}, {35, 46}, {37, 46}, {38, 46}, {39, 46}, {49, 46}, {67, 46}, {23, 45}, {28, 45}, {29, 45}, {31, 45}, {32, 45}, {40, 45}, {41, 45}, {49, 45}, {50, 45}, {68, 45}, {24, 44}, {29, 44}, {32, 44}, {41, 44}, {51, 44}, {68, 44}, {25, 43}, {30, 43}, {32, 43}, {42, 43}, {43, 43}, {51, 43}, {68, 43}, {69, 43}, {31, 42}, {32, 42}, {43, 42}, {52, 42}, {55, 42}, {26, 41}, {27, 41}, {31, 41}, {32, 41}, {33, 41}, {44, 41}, {45, 41}, {46, 41}, {47, 41}, {48, 41}, {49, 41}, {53, 41}, {25, 40}, {27, 40}, {32, 40}, {43, 40}, {44, 40}, {45, 40}, {46, 40}, {48, 40}, {49, 40}, {50, 40}, {51, 40}, {53, 40}, {56, 40}, {32, 39}, {33, 39}, {43, 39}, {50, 39}, {51, 39}, {54, 39}, {56, 39}, {69, 39}, {24, 38}, {32, 38}, {41, 38}, {42, 38}, {51, 38}, {52, 38}, {54, 38}, {57, 38}, {69, 38}, {31, 37}, {32, 37}, {40, 37}, {41, 37}, {42, 37}, {43, 37}, {44, 37}, {45, 37}, {46, 37}, {47, 37}, {48, 37}, {51, 37}, {52, 37}, {55, 37}, {57, 37}, {69, 37}, {24, 36}, {31, 36}, {32, 36}, {39, 36}, {40, 36}, {41, 36}, {42, 36}, {43, 36}, {45, 36}, {48, 36}, {49, 36}, {51, 36}, {53, 36}, {55, 36}, {58, 36}, {22, 35}, {23, 35}, {24, 35}, {25, 35}, {30, 35}, {31, 35}, {32, 35}, {39, 35}, {41, 35}, {49, 35}, {51, 35}, {55, 35}, {56, 35}, {58, 35}, {71, 35}, {20, 34}, {27, 34}, {30, 34}, {31, 34}, {51, 34}, {53, 34}, {57, 34}, {60, 34}, {18, 33}, {19, 33}, {29, 33}, {30, 33}, {31, 33}, {45, 33}, {46, 33}, {47, 33}, {52, 33}, {53, 33}, {55, 33}, {57, 33}, {58, 33}, {17, 32}, {30, 32}, {44, 32}, {47, 32}, {54, 32}, {57, 32}, {59, 32}, {61, 32}, {71, 32}, {72, 32}, {43, 31}, {47, 31}, {56, 31}, {58, 31}, {59, 31}, {61, 31}, {72, 31}, {74, 31}, {16, 30}, {43, 30}, {46, 30}, {47, 30}, {59, 30}, {63, 30}, {71, 30}, {75, 30}, {43, 29}, {46, 29}, {47, 29}, {59, 29}, {60, 29}, {75, 29}, {15, 28}, {43, 28}, {46, 28}, {61, 28}, {76, 28}, {15, 27}, {43, 27}, {44, 27}, {45, 27}, {46, 27}, {60, 27}, {62, 27}, {15, 26}, {43, 26}, {44, 26}, {46, 26}, {59, 26}, {60, 26}, {64, 26}, {77, 26}, {15, 25}, {58, 25}, {61, 25}, {77, 25}, {15, 24}, {53, 24}, {55, 24}, {61, 24}, {77, 24}, {62, 23}, {16, 22}, {61, 22}, {62, 22}, {15, 21}, {16, 21}, {52, 21}, {63, 21}, {77, 21}, {16, 20}, {17, 20}, {46, 20}, {47, 20}, {60, 20}, {62, 20}, {63, 20}, {65, 20}, {76, 20}, {15, 19}, {17, 19}, {18, 19}, {44, 19}, {45, 19}, {48, 19}, {53, 19}, {56, 19}, {60, 19}, {62, 19}, {67, 19}, {68, 19}, {76, 19}, {15, 18}, {18, 18}, {19, 18}, {20, 18}, {32, 18}, {33, 18}, {34, 18}, {41, 18}, {42, 18}, {43, 18}, {46, 18}, {48, 18}, {53, 18}, {59, 18}, {60, 18}, {69, 18}, {75, 18}, {16, 17}, {17, 17}, {20, 17}, {21, 17}, {22, 17}, {23, 17}, {24, 17}, {26, 17}, {28, 17}, {29, 17}, {30, 17}, {31, 17}, {32, 17}, {34, 17}, {35, 17}, {36, 17}, {37, 17}, {38, 17}, {39, 17}, {40, 17}, {44, 17}, {46, 17}, {48, 17}, {53, 17}, {56, 17}, {58, 17}, {75, 17}, {17, 16}, {18, 16}, {20, 16}, {24, 16}, {26, 16}, {27, 16}, {29, 16}, {33, 16}, {41, 16}, {42, 16}, {44, 16}, {47, 16}, {52, 16}, {57, 16}, {70, 16}, {73, 16}, {74, 16}, {17, 15}, {18, 15}, {20, 15}, {22, 15}, {24, 15}, {27, 15}, {29, 15}, {31, 15}, {33, 15}, {35, 15}, {36, 15}, {38, 15}, {39, 15}, {42, 15}, {45, 15}, {47, 15}, {52, 15}, {53, 15}, {55, 15}, {56, 15}, {70, 15}, {73, 15}, {17, 14}, {19, 14}, {21, 14}, {24, 14}, {26, 14}, {29, 14}, {31, 14}, {34, 14}, {37, 14}, {40, 14}, {42, 14}, {44, 14}, {46, 14}, {47, 14}, {53, 14}, {54, 14}, {55, 14}, {62, 14}, {70, 14}, {72, 14}, {17, 13}, {19, 13}, {21, 13}, {23, 13}, {25, 13}, {27, 13}, {30, 13}, {32, 13}, {34, 13}, {36, 13}, {38, 13}, {41, 13}, {43, 13}, {44, 13}, {45, 13}, {60, 13}, {70, 13}, {71, 13}, {18, 12}, {21, 12}, {23, 12}, {26, 12}, {28, 12}, {31, 12}, {34, 12}, {37, 12}, {39, 12}, {41, 12}, {42, 12}, {70, 12}, {18, 11}, {19, 11}, {20, 11}, {21, 11}, {24, 11}, {25, 11}, {27, 11}, {29, 11}, {31, 11}, {33, 11}, {35, 11}, {38, 11}, {41, 11}, {59, 11}, {26, 10}, {29, 10}, {32, 10}, {34, 10}, {36, 10}, {39, 10}, {40, 10}, {69, 10}, {21, 9}, {26, 9}, {28, 9}, {30, 9}, {32, 9}, {33, 9}, {35, 9}, {36, 9}, {37, 9}, {38, 9}, {39, 9}, {22, 8}, {27, 8}, {28, 8}, {29, 8}, {30, 8}, {31, 8}, {68, 8}, {23, 7}, {66, 7}, {24, 6}, {65, 6}, {25, 5}, {62, 5}, {63, 5}, {26, 4}, {55, 4}, {56, 4}, {57, 4}, {58, 4}, {59, 4}, {60, 4}, {61, 4}, {28, 3}, {53, 3}, {29, 2}, {50, 2}, {51, 2}, {52, 2}, {31, 1}, {32, 1}, {48, 1}
|
---|
| 858 | });
|
---|
[7442] | 859 | tspProblem.BestKnownQuality = new DoubleValue(867);
|
---|
[6476] | 860 |
|
---|
[6938] | 861 | tspProblem.EvaluatorParameter.Value = new TSPRoundedEuclideanPathEvaluator();
|
---|
| 862 | tspProblem.SolutionCreatorParameter.Value = new RandomPermutationCreator();
|
---|
[6476] | 863 | tspProblem.UseDistanceMatrix.Value = true;
|
---|
| 864 | tspProblem.Name = "Funny TSP";
|
---|
| 865 | tspProblem.Description = "Represents a symmetric Traveling Salesman Problem.";
|
---|
| 866 | #endregion
|
---|
[6544] | 867 | #region Algorithm Configuration
|
---|
[6476] | 868 | vns.Name = "Variable Neighborhood Search - TSP";
|
---|
| 869 | vns.Description = "A variable neighborhood search algorithm which solves a funny TSP instance";
|
---|
| 870 | vns.Problem = tspProblem;
|
---|
| 871 |
|
---|
| 872 | var localImprovement = vns.LocalImprovementParameter.ValidValues
|
---|
| 873 | .OfType<LocalSearchImprovementOperator>()
|
---|
| 874 | .Single();
|
---|
| 875 | // move generator has to be set first
|
---|
| 876 | localImprovement.MoveGenerator = localImprovement.MoveGeneratorParameter.ValidValues
|
---|
| 877 | .OfType<StochasticInversionMultiMoveGenerator>()
|
---|
| 878 | .Single();
|
---|
| 879 | localImprovement.MoveEvaluator = localImprovement.MoveEvaluatorParameter.ValidValues
|
---|
| 880 | .OfType<TSPInversionMoveRoundedEuclideanPathEvaluator>()
|
---|
| 881 | .Single();
|
---|
| 882 | localImprovement.MoveMaker = localImprovement.MoveMakerParameter.ValidValues
|
---|
| 883 | .OfType<InversionMoveMaker>()
|
---|
| 884 | .Single();
|
---|
| 885 | localImprovement.SampleSizeParameter.Value = new IntValue(500);
|
---|
| 886 | vns.LocalImprovement = localImprovement;
|
---|
| 887 |
|
---|
| 888 | vns.LocalImprovementMaximumIterations = 150;
|
---|
| 889 | vns.MaximumIterations = 25;
|
---|
| 890 | vns.Seed = 0;
|
---|
| 891 | vns.SetSeedRandomly = true;
|
---|
| 892 | var shakingOperator = vns.ShakingOperatorParameter.ValidValues
|
---|
| 893 | .OfType<PermutationShakingOperator>()
|
---|
| 894 | .Single();
|
---|
| 895 | shakingOperator.Operators.SetItemCheckedState(shakingOperator.Operators
|
---|
| 896 | .OfType<Swap2Manipulator>()
|
---|
| 897 | .Single(), false);
|
---|
| 898 | shakingOperator.Operators.SetItemCheckedState(shakingOperator.Operators
|
---|
| 899 | .OfType<Swap3Manipulator>()
|
---|
| 900 | .Single(), false);
|
---|
| 901 | vns.ShakingOperator = shakingOperator;
|
---|
| 902 | #endregion
|
---|
| 903 | vns.Engine = new ParallelEngine();
|
---|
| 904 | return vns;
|
---|
| 905 | }
|
---|
| 906 | #endregion
|
---|
| 907 | #endregion
|
---|
[6544] | 908 |
|
---|
| 909 | #region Helpers
|
---|
[6476] | 910 | private void ConfigureEvolutionStrategyParameters<R, M, SC, SR, SM>(EvolutionStrategy es, int popSize, int children, int parentsPerChild, int maxGens, bool plusSelection)
|
---|
| 911 | where R : ICrossover
|
---|
| 912 | where M : IManipulator
|
---|
| 913 | where SC : IStrategyParameterCreator
|
---|
| 914 | where SR : IStrategyParameterCrossover
|
---|
| 915 | where SM : IStrategyParameterManipulator {
|
---|
| 916 | es.PopulationSize.Value = popSize;
|
---|
| 917 | es.Children.Value = children;
|
---|
| 918 | es.ParentsPerChild.Value = parentsPerChild;
|
---|
| 919 | es.MaximumGenerations.Value = maxGens;
|
---|
| 920 | es.PlusSelection.Value = false;
|
---|
| 921 |
|
---|
| 922 | es.Seed.Value = 0;
|
---|
| 923 | es.SetSeedRandomly.Value = true;
|
---|
| 924 |
|
---|
| 925 | es.Recombinator = es.RecombinatorParameter.ValidValues
|
---|
| 926 | .OfType<R>()
|
---|
| 927 | .Single();
|
---|
| 928 |
|
---|
| 929 | es.Mutator = es.MutatorParameter.ValidValues
|
---|
| 930 | .OfType<M>()
|
---|
| 931 | .Single();
|
---|
| 932 |
|
---|
| 933 | es.StrategyParameterCreator = es.StrategyParameterCreatorParameter.ValidValues
|
---|
| 934 | .OfType<SC>()
|
---|
| 935 | .Single();
|
---|
| 936 | es.StrategyParameterCrossover = es.StrategyParameterCrossoverParameter.ValidValues
|
---|
| 937 | .OfType<SR>()
|
---|
| 938 | .Single();
|
---|
| 939 | es.StrategyParameterManipulator = es.StrategyParameterManipulatorParameter.ValidValues
|
---|
| 940 | .OfType<SM>()
|
---|
| 941 | .Single();
|
---|
| 942 | es.Engine = new ParallelEngine();
|
---|
| 943 | }
|
---|
| 944 |
|
---|
[6441] | 945 | private void ConfigureGeneticAlgorithmParameters<S, C, M>(GeneticAlgorithm ga, int popSize, int elites, int maxGens, double mutationRate, int tournGroupSize = 0)
|
---|
| 946 | where S : ISelector
|
---|
| 947 | where C : ICrossover
|
---|
| 948 | where M : IManipulator {
|
---|
| 949 | ga.Elites.Value = elites;
|
---|
| 950 | ga.MaximumGenerations.Value = maxGens;
|
---|
| 951 | ga.MutationProbability.Value = mutationRate;
|
---|
| 952 | ga.PopulationSize.Value = popSize;
|
---|
| 953 | ga.Seed.Value = 0;
|
---|
| 954 | ga.SetSeedRandomly.Value = true;
|
---|
| 955 | ga.Selector = ga.SelectorParameter.ValidValues
|
---|
| 956 | .OfType<S>()
|
---|
[7900] | 957 | .First();
|
---|
[6441] | 958 |
|
---|
| 959 | ga.Crossover = ga.CrossoverParameter.ValidValues
|
---|
| 960 | .OfType<C>()
|
---|
[7900] | 961 | .First();
|
---|
[6441] | 962 |
|
---|
| 963 | ga.Mutator = ga.MutatorParameter.ValidValues
|
---|
| 964 | .OfType<M>()
|
---|
[7900] | 965 | .First();
|
---|
[6441] | 966 |
|
---|
| 967 | var tSelector = ga.Selector as TournamentSelector;
|
---|
| 968 | if (tSelector != null) {
|
---|
[6476] | 969 | tSelector.GroupSizeParameter.Value.Value = tournGroupSize;
|
---|
[6441] | 970 | }
|
---|
| 971 | ga.Engine = new ParallelEngine();
|
---|
| 972 | }
|
---|
| 973 |
|
---|
[6476] | 974 | private void ConfigureIslandGeneticAlgorithmParameters<S, C, M, Mi, MiS, MiR>(IslandGeneticAlgorithm ga, int popSize, int elites, int maxGens, double mutationRate, int numberOfIslands, int migrationInterval, double migrationRate)
|
---|
| 975 | where S : ISelector
|
---|
| 976 | where C : ICrossover
|
---|
| 977 | where M : IManipulator
|
---|
| 978 | where Mi : IMigrator
|
---|
| 979 | where MiS : ISelector
|
---|
| 980 | where MiR : IReplacer {
|
---|
| 981 | ga.Elites.Value = elites;
|
---|
| 982 | ga.MaximumGenerations.Value = maxGens;
|
---|
| 983 | ga.MutationProbability.Value = mutationRate;
|
---|
| 984 | ga.PopulationSize.Value = popSize;
|
---|
| 985 | ga.NumberOfIslands.Value = numberOfIslands;
|
---|
| 986 | ga.MigrationInterval.Value = migrationInterval;
|
---|
| 987 | ga.MigrationRate.Value = migrationRate;
|
---|
| 988 | ga.Seed.Value = 0;
|
---|
| 989 | ga.SetSeedRandomly.Value = true;
|
---|
| 990 | ga.Selector = ga.SelectorParameter.ValidValues
|
---|
| 991 | .OfType<S>()
|
---|
| 992 | .Single();
|
---|
[6441] | 993 |
|
---|
[6476] | 994 | ga.Crossover = ga.CrossoverParameter.ValidValues
|
---|
| 995 | .OfType<C>()
|
---|
| 996 | .Single();
|
---|
| 997 |
|
---|
| 998 | ga.Mutator = ga.MutatorParameter.ValidValues
|
---|
| 999 | .OfType<M>()
|
---|
| 1000 | .Single();
|
---|
| 1001 | ga.Migrator = ga.MigratorParameter.ValidValues
|
---|
| 1002 | .OfType<Mi>()
|
---|
| 1003 | .Single();
|
---|
| 1004 | ga.EmigrantsSelector = ga.EmigrantsSelectorParameter.ValidValues
|
---|
| 1005 | .OfType<MiS>()
|
---|
| 1006 | .Single();
|
---|
| 1007 | ga.ImmigrationReplacer = ga.ImmigrationReplacerParameter.ValidValues
|
---|
| 1008 | .OfType<MiR>()
|
---|
| 1009 | .Single();
|
---|
| 1010 | ga.Engine = new ParallelEngine();
|
---|
| 1011 | }
|
---|
| 1012 |
|
---|
| 1013 |
|
---|
[6441] | 1014 | private void RunAlgorithm(IAlgorithm a) {
|
---|
| 1015 | var trigger = new EventWaitHandle(false, EventResetMode.ManualReset);
|
---|
| 1016 | Exception ex = null;
|
---|
| 1017 | a.Stopped += (src, e) => { trigger.Set(); };
|
---|
[6476] | 1018 | a.ExceptionOccurred += (src, e) => { ex = e.Value; trigger.Set(); };
|
---|
[6441] | 1019 | a.Prepare();
|
---|
| 1020 | a.Start();
|
---|
| 1021 | trigger.WaitOne();
|
---|
| 1022 |
|
---|
| 1023 | Assert.AreEqual(ex, null);
|
---|
| 1024 | }
|
---|
[6468] | 1025 |
|
---|
[6476] | 1026 | private double GetDoubleResult(IAlgorithm a, string resultName) {
|
---|
| 1027 | return ((DoubleValue)a.Results[resultName].Value).Value;
|
---|
[6468] | 1028 | }
|
---|
[6476] | 1029 | private int GetIntResult(IAlgorithm a, string resultName) {
|
---|
| 1030 | return ((IntValue)a.Results[resultName].Value).Value;
|
---|
[6468] | 1031 | }
|
---|
[6476] | 1032 | #endregion
|
---|
[6441] | 1033 | }
|
---|
| 1034 | }
|
---|