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source: branches/GeneralizedQAP/UnitTests/CordeauCrossoverTest.cs @ 12391

Last change on this file since 12391 was 7970, checked in by abeham, 12 years ago

#1614: restructured architecture to allow for different evaluator with different penalty strategies

File size: 2.5 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2012 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 System.Linq;
23using HeuristicLab.Data;
24using HeuristicLab.Encodings.IntegerVectorEncoding;
25using HeuristicLab.Problems.GeneralizedQuadraticAssignment;
26using HeuristicLab.Problems.Instances.CordeauGQAP;
27using HeuristicLab.Random;
28using Microsoft.VisualStudio.TestTools.UnitTesting;
29
30namespace UnitTests {
31  [TestClass]
32  public class CordeauCrossoverTest {
33    [TestMethod]
34    public void CordeauCrossoverFunctionalityTest() {
35      var provider = new CordeauGQAPInstanceProvider();
36      var instance = provider.LoadData(provider.GetDataDescriptors().First());
37      var gqap = new GeneralizedQuadraticAssignmentProblem();
38      gqap.Load(instance);
39
40      var random = new MersenneTwister();
41      for (int i = 0; i < 100; i++) {
42        var parent1 = new IntegerVector(gqap.Demands.Length, random, 0, gqap.Capacities.Length);
43        var parent2 = new IntegerVector(gqap.Demands.Length, random, 0, gqap.Capacities.Length);
44
45        try {
46          CordeauCrossover.Apply(random, gqap.Maximization,
47            parent1,
48            new DoubleValue(gqap.Evaluator.Evaluate(parent1, gqap.Weights, gqap.Distances, gqap.InstallationCosts, gqap.Demands, gqap.Capacities, gqap.TransportationCosts, gqap.ExpectedRandomQuality)),
49            parent2,
50            new DoubleValue(gqap.Evaluator.Evaluate(parent2, gqap.Weights, gqap.Distances, gqap.InstallationCosts, gqap.Demands, gqap.Capacities, gqap.TransportationCosts, gqap.ExpectedRandomQuality)),
51            gqap.Weights, gqap.Distances, gqap.InstallationCosts, gqap.Demands, gqap.Capacities, gqap.TransportationCosts, gqap.ExpectedRandomQuality, gqap.Evaluator);
52        } catch {
53          Assert.Fail("Error during crossover");
54        }
55      }
56    }
57  }
58}
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