1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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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.IO;
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23 | using System.Linq;
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24 | using HEAL.Attic;
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25 | using HeuristicLab.Algorithms.ALPS;
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26 | using HeuristicLab.Encodings.PermutationEncoding;
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27 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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28 | using HeuristicLab.Problems.DataAnalysis.Symbolic;
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29 | using HeuristicLab.Problems.DataAnalysis.Symbolic.Regression;
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30 | using HeuristicLab.Problems.Instances.DataAnalysis;
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31 | using HeuristicLab.Problems.Instances.TSPLIB;
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32 | using HeuristicLab.Problems.TravelingSalesman;
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33 | using HeuristicLab.Selection;
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34 | using Microsoft.VisualStudio.TestTools.UnitTesting;
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35 |
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36 | namespace HeuristicLab.Tests {
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37 | [TestClass]
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38 | public class AlpsTspSampleTest {
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39 | private const string TspSampleFileName = "ALPSGA_TSP";
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40 | private const string SymRegSampleFileName = "ALPSGP_SymReg";
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41 |
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42 | private static readonly ProtoBufSerializer serializer = new ProtoBufSerializer();
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43 |
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44 | [TestMethod]
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45 | [TestCategory("Samples.Create")]
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46 | [TestProperty("Time", "medium")]
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47 | public void CreateAlpsGaTspSampleTest() {
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48 | var alpsGa = CreateAlpsGaTspSample();
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49 | string path = Path.Combine(SamplesUtils.SamplesDirectory, TspSampleFileName + SamplesUtils.SampleFileExtension);
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50 | serializer.Serialize(alpsGa, path);
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51 | }
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52 |
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53 | [TestMethod]
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54 | [TestCategory("Samples.Create")]
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55 | [TestProperty("Time", "medium")]
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56 | public void CreateAlpsGaSymRegSampleTest() {
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57 | var alpsGa = CreateAlpsGaSymRegSample();
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58 | string path = Path.Combine(SamplesUtils.SamplesDirectory, SymRegSampleFileName + SamplesUtils.SampleFileExtension);
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59 | serializer.Serialize(alpsGa, path);
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60 | }
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61 |
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62 | [TestMethod]
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63 | [TestCategory("Samples.Execute")]
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64 | [TestProperty("Time", "long")]
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65 | public void RunAlpsGaTspSampleTest() {
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66 | var alpsGa = CreateAlpsGaTspSample();
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67 | alpsGa.SetSeedRandomly.Value = false;
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68 | SamplesUtils.RunAlgorithm(alpsGa);
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69 | Assert.AreEqual(7967, SamplesUtils.GetDoubleResult(alpsGa, "BestQuality"));
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70 | Assert.AreEqual(17565.174444444445, SamplesUtils.GetDoubleResult(alpsGa, "CurrentAverageQuality"));
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71 | Assert.AreEqual(50295, SamplesUtils.GetDoubleResult(alpsGa, "CurrentWorstQuality"));
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72 | Assert.AreEqual(621900, SamplesUtils.GetIntResult(alpsGa, "EvaluatedSolutions"));
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73 | }
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74 |
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75 | [TestMethod]
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76 | [TestCategory("Samples.Execute")]
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77 | [TestProperty("Time", "long")]
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78 | public void RunAlpsGaSymRegSampleTest() {
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79 | var alpsGa = CreateAlpsGaSymRegSample();
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80 | alpsGa.SetSeedRandomly.Value = false;
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81 | SamplesUtils.RunAlgorithm(alpsGa);
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82 | Assert.AreEqual(265855, SamplesUtils.GetIntResult(alpsGa, "EvaluatedSolutions"));
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83 | }
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84 |
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85 | private AlpsGeneticAlgorithm CreateAlpsGaTspSample() {
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86 | AlpsGeneticAlgorithm alpsGa = new AlpsGeneticAlgorithm();
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87 | #region Problem Configuration
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88 | var provider = new TSPLIBTSPInstanceProvider();
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89 | var instance = provider.GetDataDescriptors().Single(x => x.Name == "ch130");
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90 | TravelingSalesmanProblem tspProblem = new TravelingSalesmanProblem();
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91 | tspProblem.Load(provider.LoadData(instance));
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92 | tspProblem.UseDistanceMatrix.Value = true;
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93 | #endregion
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94 | #region Algorithm Configuration
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95 | alpsGa.Name = "ALPS Genetic Algorithm - TSP";
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96 | alpsGa.Description = "An age-layered population structure genetic algorithm which solves the \"ch130\" traveling salesman problem (imported from TSPLIB)";
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97 | alpsGa.Problem = tspProblem;
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98 | SamplesUtils.ConfigureAlpsGeneticAlgorithmParameters<GeneralizedRankSelector, MultiPermutationCrossover, InversionManipulator>(alpsGa,
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99 | numberOfLayers: 1000,
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100 | popSize: 100,
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101 | mutationRate: 0.05,
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102 | elites: 1,
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103 | plusSelection: true,
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104 | agingScheme: AgingScheme.Polynomial,
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105 | ageGap: 20,
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106 | ageInheritance: 1.0,
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107 | maxGens: 1000);
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108 | var checkedCrossovers = new[] { typeof(EdgeRecombinationCrossover), typeof(MaximalPreservativeCrossover), typeof(OrderCrossover2) };
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109 | var multiCrossover = (MultiPermutationCrossover)alpsGa.Crossover;
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110 | var crossovers = multiCrossover.Operators.Where(c => checkedCrossovers.Any(cc => cc.IsInstanceOfType(c))).ToList();
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111 | foreach (var c in multiCrossover.Operators)
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112 | multiCrossover.Operators.SetItemCheckedState(c, crossovers.Contains(c));
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113 | #endregion
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114 | return alpsGa;
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115 | }
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116 |
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117 | private AlpsGeneticAlgorithm CreateAlpsGaSymRegSample() {
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118 | AlpsGeneticAlgorithm alpsGa = new AlpsGeneticAlgorithm();
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119 | #region Problem Configuration
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120 | var provider = new VladislavlevaInstanceProvider();
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121 | var instance = provider.GetDataDescriptors().Single(x => x.Name.StartsWith("Vladislavleva-5 F5"));
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122 | var symbRegProblem = new SymbolicRegressionSingleObjectiveProblem();
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123 | symbRegProblem.Load(provider.LoadData(instance));
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124 |
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125 | symbRegProblem.MaximumSymbolicExpressionTreeDepth.Value = 35;
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126 | symbRegProblem.MaximumSymbolicExpressionTreeLength.Value = 35;
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127 |
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128 | var grammar = (TypeCoherentExpressionGrammar)symbRegProblem.SymbolicExpressionTreeGrammar;
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129 | grammar.Symbols.OfType<Exponential>().Single().Enabled = false;
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130 | grammar.Symbols.OfType<Logarithm>().Single().Enabled = false;
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131 |
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132 | #endregion
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133 | #region Algorithm Configuration
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134 | alpsGa.Name = "ALPS Genetic Programming - Symbolic Regression";
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135 | alpsGa.Description = "An ALPS-GP to solve a symbolic regression problem (Vladislavleva-5 dataset)";
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136 | alpsGa.Problem = symbRegProblem;
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137 | SamplesUtils.ConfigureAlpsGeneticAlgorithmParameters<GeneralizedRankSelector, SubtreeCrossover, MultiSymbolicExpressionTreeManipulator>(alpsGa,
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138 | numberOfLayers: 1000,
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139 | popSize: 100,
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140 | mutationRate: 0.25,
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141 | elites: 1,
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142 | plusSelection: false,
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143 | agingScheme: AgingScheme.Polynomial,
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144 | ageGap: 15,
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145 | ageInheritance: 1.0,
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146 | maxGens: 500);
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147 | #endregion
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148 | return alpsGa;
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149 | }
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150 | }
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151 | }
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