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source: stable/HeuristicLab.Tests/HeuristicLab.Encodings.PermutationEncoding-3.3/EdgeRecombinationCrossoverTest.cs @ 17698

Last change on this file since 17698 was 17181, checked in by swagner, 5 years ago

#2875: Merged r17180 from trunk to stable

File size: 2.9 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using HeuristicLab.Tests;
23using Microsoft.VisualStudio.TestTools.UnitTesting;
24
25namespace HeuristicLab.Encodings.PermutationEncoding.Tests {
26  /// <summary>
27  ///This is a test class for EdgeRecombinationCrossover and is intended
28  ///to contain all EdgeRecombinationCrossover Unit Tests
29  ///</summary>
30  [TestClass()]
31  public class EdgeRecombinationCrossoverTest {
32    /// <summary>
33    ///A test for Apply
34    ///</summary>
35    [TestMethod]
36    [TestCategory("Encodings.Permutation")]
37    [TestProperty("Time", "short")]
38    public void EdgeRecombinationCrossoverApplyTest() {
39      TestRandom random = new TestRandom();
40      Permutation parent1, parent2, expected, actual;
41      // The following test is based on an example from Eiben, A.E. and Smith, J.E. 2003. Introduction to Evolutionary Computation. Natural Computing Series, Springer-Verlag Berlin Heidelberg, pp. 54-55
42      random.Reset();
43      random.IntNumbers = new int[] { 0 };
44      random.DoubleNumbers = new double[] { 0.5, 0, 0, 0 };
45      parent1 = new Permutation(PermutationTypes.RelativeUndirected, new int[] { 0, 1, 2, 3, 4, 5, 6, 7, 8 });
46      Assert.IsTrue(parent1.Validate());
47      parent2 = new Permutation(PermutationTypes.RelativeUndirected, new int[] { 8, 2, 6, 7, 1, 5, 4, 0, 3 });
48      Assert.IsTrue(parent2.Validate());
49      expected = new Permutation(PermutationTypes.RelativeUndirected, new int[] { 0, 4, 5, 1, 7, 6, 2, 8, 3 });
50      Assert.IsTrue(expected.Validate());
51      actual = EdgeRecombinationCrossover.Apply(random, parent1, parent2);
52      Assert.IsTrue(actual.Validate());
53      Assert.IsTrue(Auxiliary.PermutationIsEqualByPosition(expected, actual));
54
55      // perform a test when the two permutations are of unequal length
56      random.Reset();
57      bool exceptionFired = false;
58      try {
59        EdgeRecombinationCrossover.Apply(random, new Permutation(PermutationTypes.RelativeUndirected, 8), new Permutation(PermutationTypes.RelativeUndirected, 6));
60      }
61      catch (System.ArgumentException) {
62        exceptionFired = true;
63      }
64      Assert.IsTrue(exceptionFired);
65    }
66  }
67}
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