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source: trunk/sources/HeuristicLab.Permutation/3.3/Tests/MaximalPreservativeCrossoverTest.cs @ 2879

Last change on this file since 2879 was 2867, checked in by abeham, 14 years ago

Added tests from our book for OX, PMX and CX.
Corrected a mistake in the MPX test regarding the name of one test
The tests currently fail with the new implementations.
#889

File size: 4.8 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2010 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.Permutation;
23using Microsoft.VisualStudio.TestTools.UnitTesting;
24using HeuristicLab.Core;
25
26namespace HeuristicLab.Permutation.Tests {
27
28
29  /// <summary>
30  ///This is a test class for MaximalPreservativeCrossover and is intended
31  ///to contain all MaximalPreservativeCrossover Unit Tests
32  ///</summary>
33  [TestClass()]
34  public class MaximalPreservativeCrossoverTest {
35
36
37    private TestContext testContextInstance;
38
39    /// <summary>
40    ///Gets or sets the test context which provides
41    ///information about and functionality for the current test run.
42    ///</summary>
43    public TestContext TestContext {
44      get {
45        return testContextInstance;
46      }
47      set {
48        testContextInstance = value;
49      }
50    }
51
52    #region Additional test attributes
53    //
54    //You can use the following additional attributes as you write your tests:
55    //
56    //Use ClassInitialize to run code before running the first test in the class
57    //[ClassInitialize()]
58    //public static void MyClassInitialize(TestContext testContext)
59    //{
60    //}
61    //
62    //Use ClassCleanup to run code after all tests in a class have run
63    //[ClassCleanup()]
64    //public static void MyClassCleanup()
65    //{
66    //}
67    //
68    //Use TestInitialize to run code before running each test
69    //[TestInitialize()]
70    //public void MyTestInitialize()
71    //{
72    //}
73    //
74    //Use TestCleanup to run code after each test has run
75    //[TestCleanup()]
76    //public void MyTestCleanup()
77    //{
78    //}
79    //
80    #endregion
81
82
83    /// <summary>
84    ///A test for Cross
85    ///</summary>
86    [TestMethod()]
87    [DeploymentItem("HeuristicLab.Permutation-3.3.dll")]
88    public void MaximalPreservativeCrossoverCrossTest() {
89      TestRandom random = new TestRandom();
90      MaximalPreservativeCrossover_Accessor target =
91        new MaximalPreservativeCrossover_Accessor(new PrivateObject(typeof(MaximalPreservativeCrossover)));
92      // perform a test with more than two parents
93      random.Reset();
94      bool exceptionFired = false;
95      try {
96        target.Cross(random, new ItemArray<Permutation>(new Permutation[] {
97          new Permutation(4), new Permutation(4), new Permutation(4)}));
98      }
99      catch (System.InvalidOperationException) {
100        exceptionFired = true;
101      }
102      Assert.IsTrue(exceptionFired);
103    }
104
105    /// <summary>
106    ///A test for Apply
107    ///</summary>
108    [TestMethod()]
109    public void MaximalPreservativeCrossoverApplyTest() {
110      TestRandom random = new TestRandom();
111      Permutation parent1, parent2, expected, actual;
112      // The following test is based on an example from Larranaga, 1999. Genetic Algorithms for the Traveling Salesman Problem.
113      random.Reset();
114      random.IntNumbers = new int[] { 3, 2 };
115      parent1 = new Permutation(new int[] { 0, 1, 2, 3, 4, 5, 6, 7 });
116      Assert.IsTrue(parent1.Validate());
117      parent2 = new Permutation(new int[] { 1, 3, 5, 7, 6, 4, 2, 0 });
118      Assert.IsTrue(parent2.Validate());
119      expected = new Permutation(new int[] { 1, 0, 2, 3, 4, 5, 7, 6 });
120      Assert.IsTrue(expected.Validate());
121      actual = MaximalPreservativeCrossover.Apply(random, parent1, parent2);
122      Assert.IsTrue(actual.Validate());
123      Assert.IsTrue(Auxiliary.PermutationIsEqualByPosition(expected, actual));
124     
125      // perform a test when the two permutations are of unequal length
126      random.Reset();
127      bool exceptionFired = false;
128      try {
129        MaximalPreservativeCrossover.Apply(random, new Permutation(8), new Permutation(6));
130      }
131      catch (System.ArgumentException) {
132        exceptionFired = true;
133      }
134      Assert.IsTrue(exceptionFired);
135    }
136
137    /// <summary>
138    ///A test for OrderCrossover Constructor
139    ///</summary>
140    [TestMethod()]
141    public void MaximalPreservativeCrossoverConstructorTest() {
142      MaximalPreservativeCrossover target = new MaximalPreservativeCrossover();
143    }
144  }
145}
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