| 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) 2002-2015 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 HeuristicLab.Algorithms.ALPS;
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| 25 | using HeuristicLab.Encodings.PermutationEncoding;
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| 26 | using HeuristicLab.Persistence.Default.Xml;
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| 27 | using HeuristicLab.Problems.Instances.TSPLIB;
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| 28 | using HeuristicLab.Problems.TravelingSalesman;
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| 29 | using HeuristicLab.Selection;
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| 30 | using Microsoft.VisualStudio.TestTools.UnitTesting;
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| 31 |
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| 32 | namespace HeuristicLab.Tests {
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| 33 | [TestClass]
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| 34 | public class AlpsTspSampleTest {
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| 35 | private const string SampleFileName = "ALPSGA_TSP";
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| 36 |
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| 37 | [TestMethod]
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| 38 | [TestCategory("Samples.Create")]
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| 39 | [TestProperty("Time", "medium")]
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| 40 | public void CreateAlpsGaTspSampleTest() {
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| 41 | var alpsGa = CreateAlpsGaTspSample();
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| 42 | string path = Path.Combine(SamplesUtils.SamplesDirectory, SampleFileName + SamplesUtils.SampleFileExtension);
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| 43 | XmlGenerator.Serialize(alpsGa, path);
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| 44 | }
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| 45 | [TestMethod]
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| 46 | [TestCategory("Samples.Execute")]
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| 47 | [TestProperty("Time", "long")]
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| 48 | public void RunAlpsGaTspSampleTest() {
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| 49 | var alpsGaE = CreateAlpsGaTspSample(plusSelection: false);
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| 50 | alpsGaE.SetSeedRandomly.Value = false;
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| 51 | SamplesUtils.RunAlgorithm(alpsGaE);
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| 52 | Assert.AreEqual(23661, SamplesUtils.GetDoubleResult(alpsGaE, "BestQuality"));
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| 53 | Assert.AreEqual(35131.1625, SamplesUtils.GetDoubleResult(alpsGaE, "CurrentAverageQuality"));
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| 54 | Assert.AreEqual(49699, SamplesUtils.GetDoubleResult(alpsGaE, "CurrentWorstQuality"));
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| 55 | Assert.AreEqual(26640, SamplesUtils.GetIntResult(alpsGaE, "EvaluatedSolutions"));
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| 56 |
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| 57 | var alpsGaPs = CreateAlpsGaTspSample(plusSelection: true);
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| 58 | alpsGaPs.SetSeedRandomly.Value = false;
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| 59 | SamplesUtils.RunAlgorithm(alpsGaPs);
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| 60 | Assert.AreEqual(21365, SamplesUtils.GetDoubleResult(alpsGaPs, "BestQuality"));
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| 61 | Assert.AreEqual(30774.695, SamplesUtils.GetDoubleResult(alpsGaPs, "CurrentAverageQuality"));
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| 62 | Assert.AreEqual(49699, SamplesUtils.GetDoubleResult(alpsGaPs, "CurrentWorstQuality"));
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| 63 | Assert.AreEqual(26900, SamplesUtils.GetIntResult(alpsGaPs, "EvaluatedSolutions"));
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| 64 | }
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| 65 |
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| 66 | private AlpsGeneticAlgorithm CreateAlpsGaTspSample(bool plusSelection = false) {
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| 67 | AlpsGeneticAlgorithm alpsGa = new AlpsGeneticAlgorithm();
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| 68 | #region Problem Configuration
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| 69 | var provider = new TSPLIBTSPInstanceProvider();
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| 70 | var instance = provider.GetDataDescriptors().Single(x => x.Name == "ch130");
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| 71 | TravelingSalesmanProblem tspProblem = new TravelingSalesmanProblem();
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| 72 | tspProblem.Load(provider.LoadData(instance));
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| 73 | tspProblem.UseDistanceMatrix.Value = true;
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| 74 | #endregion
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| 75 | #region Algorithm Configuration
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| 76 | alpsGa.Name = "ALPS Genetic Algorithm - TSP";
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| 77 | alpsGa.Description = "An age-layered population structure genetic algorithm which solves the \"ch130\" traveling salesman problem (imported from TSPLIB)";
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| 78 | alpsGa.Problem = tspProblem;
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| 79 | SamplesUtils.ConfigureAlpsGeneticAlgorithmParameters<GeneralizedRankSelector, OrderCrossover2, InversionManipulator>(alpsGa,
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| 80 | numberOfLayers: 10,
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| 81 | popSize: 100,
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| 82 | mutationRate: 0.05,
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| 83 | elites: 1,
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| 84 | plusSelection: plusSelection,
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| 85 | agingScheme: AgingScheme.Polynomial,
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| 86 | ageGap: 20,
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| 87 | ageInheritance: 1.0,
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| 88 | maxGens: 100);
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| 89 | #endregion
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| 90 | return alpsGa;
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| 91 | }
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| 92 | }
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| 93 | }
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