[11450] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[15583] | 3 | * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[11450] | 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.Linq;
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| 23 | using HeuristicLab.Algorithms.GeneticAlgorithm;
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| 24 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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| 25 | using HeuristicLab.Selection;
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| 26 | using Microsoft.VisualStudio.TestTools.UnitTesting;
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| 27 |
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| 28 | namespace HeuristicLab.Tests {
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| 29 | [TestClass]
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| 30 | public class GPLawnMowerSampleTest {
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| 31 | [TestMethod]
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| 32 | [TestCategory("Samples.Execute")]
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| 33 | [TestProperty("Time", "long")]
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| 34 | public void RunGpLawnMowerSampleTest() {
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| 35 | var ga = CreateGpLawnMowerSample();
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| 36 | ga.SetSeedRandomly.Value = false;
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| 37 | SamplesUtils.RunAlgorithm(ga);
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[13057] | 38 | Assert.AreEqual(55, SamplesUtils.GetDoubleResult(ga, "BestQuality"));
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[13058] | 39 | Assert.AreEqual(49.266, SamplesUtils.GetDoubleResult(ga, "CurrentAverageQuality"));
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[13057] | 40 | Assert.AreEqual(1, SamplesUtils.GetDoubleResult(ga, "CurrentWorstQuality"));
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| 41 | Assert.AreEqual(50950, SamplesUtils.GetIntResult(ga, "EvaluatedSolutions"));
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[11450] | 42 | }
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| 43 |
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| 44 | public GeneticAlgorithm CreateGpLawnMowerSample() {
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| 45 | GeneticAlgorithm ga = new GeneticAlgorithm();
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| 46 |
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| 47 | #region Problem Configuration
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| 48 |
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[13057] | 49 | var problem = new Problems.GeneticProgramming.LawnMower.Problem();
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[11450] | 50 |
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| 51 | #endregion
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| 52 | #region Algorithm Configuration
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| 53 |
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| 54 | ga.Name = "Genetic Programming - Lawn Mower";
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| 55 | ga.Description = "A standard genetic programming algorithm to solve the lawn mower problem";
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| 56 | ga.Problem = problem;
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| 57 | SamplesUtils
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| 58 | .ConfigureGeneticAlgorithmParameters
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| 59 | <TournamentSelector, SubtreeCrossover, MultiSymbolicExpressionTreeArchitectureManipulator>(
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| 60 | ga, 1000, 1, 50, 0.25, 5);
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| 61 | var mutator = (MultiSymbolicExpressionTreeArchitectureManipulator)ga.Mutator;
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| 62 | mutator.Operators.SetItemCheckedState(mutator.Operators
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| 63 | .OfType<OnePointShaker>()
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| 64 | .Single(), false);
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| 65 |
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| 66 | #endregion
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| 67 |
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| 68 | return ga;
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| 69 | }
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| 70 | }
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| 71 | }
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