[2854] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[12012] | 3 | * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[2854] | 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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[6891] | 22 | using HeuristicLab.Tests;
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[2854] | 23 | using Microsoft.VisualStudio.TestTools.UnitTesting;
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| 24 |
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[9764] | 25 | namespace HeuristicLab.Encodings.PermutationEncoding.Tests {
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[2854] | 26 | /// <summary>
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| 27 | ///This is a test class for MaximalPreservativeCrossover and is intended
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| 28 | ///to contain all MaximalPreservativeCrossover Unit Tests
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| 29 | ///</summary>
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| 30 | [TestClass()]
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| 31 | public class MaximalPreservativeCrossoverTest {
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| 32 | /// <summary>
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| 33 | ///A test for Apply
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| 34 | ///</summary>
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[9767] | 35 | [TestMethod]
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[9777] | 36 | [TestCategory("Encodings.Permutation")]
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| 37 | [TestProperty("Time", "short")]
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[2854] | 38 | public void MaximalPreservativeCrossoverApplyTest() {
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| 39 | TestRandom random = new TestRandom();
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[3053] | 40 | Permutation parent1, parent2, expected, actual;
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[2854] | 41 | // The following test is based on an example from Larranaga, 1999. Genetic Algorithms for the Traveling Salesman Problem.
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| 42 | random.Reset();
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| 43 | random.IntNumbers = new int[] { 3, 2 };
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[3231] | 44 | parent1 = new Permutation(PermutationTypes.RelativeUndirected, new int[] { 0, 1, 2, 3, 4, 5, 6, 7 });
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[2854] | 45 | Assert.IsTrue(parent1.Validate());
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[3231] | 46 | parent2 = new Permutation(PermutationTypes.RelativeUndirected, new int[] { 1, 3, 5, 7, 6, 4, 2, 0 });
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[2854] | 47 | Assert.IsTrue(parent2.Validate());
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[3231] | 48 | expected = new Permutation(PermutationTypes.RelativeUndirected, new int[] { 1, 0, 2, 3, 4, 5, 7, 6 });
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[2854] | 49 | Assert.IsTrue(expected.Validate());
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| 50 | actual = MaximalPreservativeCrossover.Apply(random, parent1, parent2);
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| 51 | Assert.IsTrue(actual.Validate());
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| 52 | Assert.IsTrue(Auxiliary.PermutationIsEqualByPosition(expected, actual));
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[4068] | 53 |
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[2854] | 54 | // perform a test when the two permutations are of unequal length
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| 55 | random.Reset();
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| 56 | bool exceptionFired = false;
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| 57 | try {
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[3231] | 58 | MaximalPreservativeCrossover.Apply(random, new Permutation(PermutationTypes.RelativeUndirected, 8), new Permutation(PermutationTypes.RelativeUndirected, 6));
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[13235] | 59 | }
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| 60 | catch (System.ArgumentException) {
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[2854] | 61 | exceptionFired = true;
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| 62 | }
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| 63 | Assert.IsTrue(exceptionFired);
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| 64 | }
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| 65 | }
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| 66 | }
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