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source: trunk/sources/HeuristicLab.Encodings.PermutationEncoding/3.3/Tests/OrderCrossoverTest.cs @ 5728

Last change on this file since 5728 was 5445, checked in by swagner, 14 years ago

Updated year of copyrights (#1406)

File size: 8.3 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2011 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.Core;
23using HeuristicLab.Encodings.PermutationEncoding;
24using Microsoft.VisualStudio.TestTools.UnitTesting;
25
26namespace HeuristicLab.Encodings.PermutationEncoding_33.Tests {
27  /// <summary>
28  ///This is a test class for OrderCrossoverTest and is intended
29  ///to contain all OrderCrossoverTest Unit Tests
30  ///</summary>
31  [TestClass()]
32  public class OrderCrossoverTest {
33
34
35    private TestContext testContextInstance;
36
37    /// <summary>
38    ///Gets or sets the test context which provides
39    ///information about and functionality for the current test run.
40    ///</summary>
41    public TestContext TestContext {
42      get {
43        return testContextInstance;
44      }
45      set {
46        testContextInstance = value;
47      }
48    }
49
50    #region Additional test attributes
51    //
52    //You can use the following additional attributes as you write your tests:
53    //
54    //Use ClassInitialize to run code before running the first test in the class
55    //[ClassInitialize()]
56    //public static void MyClassInitialize(TestContext testContext)
57    //{
58    //}
59    //
60    //Use ClassCleanup to run code after all tests in a class have run
61    //[ClassCleanup()]
62    //public static void MyClassCleanup()
63    //{
64    //}
65    //
66    //Use TestInitialize to run code before running each test
67    //[TestInitialize()]
68    //public void MyTestInitialize()
69    //{
70    //}
71    //
72    //Use TestCleanup to run code after each test has run
73    //[TestCleanup()]
74    //public void MyTestCleanup()
75    //{
76    //}
77    //
78    #endregion
79
80
81    /// <summary>
82    ///A test for Cross
83    ///</summary>
84    [TestMethod()]
85    [DeploymentItem("HeuristicLab.Encodings.PermutationEncoding-3.3.dll")]
86    public void OrderCrossoverCrossTest() {
87      TestRandom random = new TestRandom();
88      OrderCrossover_Accessor target =
89        new OrderCrossover_Accessor(new PrivateObject(typeof(OrderCrossover)));
90      // perform a test with more than two parents
91      random.Reset();
92      bool exceptionFired = false;
93      try {
94        target.Cross(random, new ItemArray<Permutation>(new Permutation[] {
95          new Permutation(PermutationTypes.RelativeUndirected, 4), new Permutation(PermutationTypes.RelativeUndirected, 4), new Permutation(PermutationTypes.RelativeUndirected, 4)}));
96      }
97      catch (System.InvalidOperationException) {
98        exceptionFired = true;
99      }
100      Assert.IsTrue(exceptionFired);
101    }
102
103    /// <summary>
104    ///A test for Apply
105    ///</summary>
106    [TestMethod()]
107    public void OrderCrossoverApplyTest() {
108      TestRandom random = new TestRandom();
109      Permutation parent1, parent2, expected, actual;
110      // 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. 55-56
111      random.Reset();
112      random.IntNumbers = new int[] { 3, 6 };
113      parent1 = new Permutation(PermutationTypes.RelativeUndirected, new int[] { 0, 1, 2, 3, 4, 5, 6, 7, 8 });
114      Assert.IsTrue(parent1.Validate());
115      parent2 = new Permutation(PermutationTypes.RelativeUndirected, new int[] { 8, 2, 6, 7, 1, 5, 4, 0, 3 });
116      Assert.IsTrue(parent2.Validate());
117      expected = new Permutation(PermutationTypes.RelativeUndirected, new int[] { 2, 7, 1, 3, 4, 5, 6, 0, 8 });
118      Assert.IsTrue(expected.Validate());
119      actual = OrderCrossover.Apply(random, parent1, parent2);
120      Assert.IsTrue(actual.Validate());
121      Assert.IsTrue(Auxiliary.PermutationIsEqualByPosition(expected, actual));
122      // The following test is based on an example from Larranaga, P. et al. 1999. Genetic Algorithms for the Travelling Salesman Problem: A Review of Representations and Operators. Artificial Intelligence Review, 13, pp. 129-170.
123      random.Reset();
124      random.IntNumbers = new int[] { 2, 4 };
125      parent1 = new Permutation(PermutationTypes.RelativeUndirected, new int[] { 0, 1, 2, 3, 4, 5, 6, 7 });
126      Assert.IsTrue(parent1.Validate());
127      parent2 = new Permutation(PermutationTypes.RelativeUndirected, new int[] { 1, 3, 5, 7, 6, 4, 2, 0 });
128      Assert.IsTrue(parent2.Validate());
129      expected = new Permutation(PermutationTypes.RelativeUndirected, new int[] { 7, 6, 2, 3, 4, 0, 1, 5 });
130      actual = OrderCrossover.Apply(random, parent1, parent2);
131      Assert.IsTrue(actual.Validate());
132      Assert.IsTrue(Auxiliary.PermutationIsEqualByPosition(expected, actual));
133      // The following test is based on an example from Talbi, E.G. 2009. Metaheuristics - From Design to Implementation. Wiley, p. 218.
134      random.Reset();
135      random.IntNumbers = new int[] { 2, 5 };
136      parent1 = new Permutation(PermutationTypes.RelativeUndirected, new int[] { 0, 1, 2, 3, 4, 5, 6, 7, 8 });
137      Assert.IsTrue(parent1.Validate());
138      parent2 = new Permutation(PermutationTypes.RelativeUndirected, new int[] { 7, 3, 0, 4, 8, 2, 5, 1, 6 });
139      Assert.IsTrue(parent2.Validate());
140      expected = new Permutation(PermutationTypes.RelativeUndirected, new int[] { 0, 8, 2, 3, 4, 5, 1, 6, 7 });
141      Assert.IsTrue(expected.Validate());
142      actual = OrderCrossover.Apply(random, parent1, parent2);
143      Assert.IsTrue(actual.Validate());
144      Assert.IsTrue(Auxiliary.PermutationIsEqualByPosition(expected, actual));
145      // The following test is not based on published examples
146      random.Reset();
147      random.IntNumbers = new int[] { 0, 5 };
148      parent1 = new Permutation(PermutationTypes.RelativeUndirected, new int[] { 2, 1, 4, 3, 7, 8, 6, 0, 5, 9 });
149      Assert.IsTrue(parent1.Validate());
150      parent2 = new Permutation(PermutationTypes.RelativeUndirected, new int[] { 5, 3, 4, 0, 9, 8, 2, 7, 1, 6 });
151      Assert.IsTrue(parent2.Validate());
152      expected = new Permutation(PermutationTypes.RelativeUndirected, new int[] { 2, 1, 4, 3, 7, 8, 6, 5, 0, 9 });
153      Assert.IsTrue(expected.Validate());
154      actual = OrderCrossover.Apply(random, parent1, parent2);
155      Assert.IsTrue(actual.Validate());
156      Assert.IsTrue(Auxiliary.PermutationIsEqualByPosition(expected, actual));
157      // based on the previous with changed breakpoints
158      random.Reset();
159      random.IntNumbers = new int[] { 6, 9 };
160      expected = new Permutation(PermutationTypes.RelativeUndirected, new int[] { 3, 4, 8, 2, 7, 1, 6, 0, 5, 9 });
161      Assert.IsTrue(expected.Validate());
162      actual = OrderCrossover.Apply(random, parent1, parent2);
163      Assert.IsTrue(actual.Validate());
164      Assert.IsTrue(Auxiliary.PermutationIsEqualByPosition(expected, actual));
165      // another one based on the previous with changed breakpoints
166      random.Reset();
167      random.IntNumbers = new int[] { 0, 9 };
168      expected = new Permutation(PermutationTypes.RelativeUndirected, new int[] { 2, 1, 4, 3, 7, 8, 6, 0, 5, 9 });
169      Assert.IsTrue(expected.Validate());
170      actual = OrderCrossover.Apply(random, parent1, parent2);
171      Assert.IsTrue(actual.Validate());
172      Assert.IsTrue(Auxiliary.PermutationIsEqualByPosition(expected, actual));
173
174      // perform a test when the two permutations are of unequal length
175      random.Reset();
176      bool exceptionFired = false;
177      try {
178        OrderCrossover.Apply(random, new Permutation(PermutationTypes.RelativeUndirected, 8), new Permutation(PermutationTypes.RelativeUndirected, 6));
179      }
180      catch (System.ArgumentException) {
181        exceptionFired = true;
182      }
183      Assert.IsTrue(exceptionFired);
184    }
185  }
186}
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