source: stable/HeuristicLab.Tests/HeuristicLab-3.3/Samples/GPLawnMowerSampleTest.cs @ 12009

Last change on this file since 12009 was 12009, checked in by ascheibe, 4 years ago

#2212 updated copyright year

File size: 2.3 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2015 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.Algorithms.GeneticAlgorithm;
24using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
25using HeuristicLab.Selection;
26using Microsoft.VisualStudio.TestTools.UnitTesting;
27
28namespace HeuristicLab.Tests {
29  [TestClass]
30  public class GPLawnMowerSampleTest {
31    [TestMethod]
32    [TestCategory("Samples.Execute")]
33    [TestProperty("Time", "long")]
34    public void RunGpLawnMowerSampleTest() {
35      var ga = CreateGpLawnMowerSample();
36      ga.SetSeedRandomly.Value = false;
37      SamplesUtils.RunAlgorithm(ga);
38    }
39
40    public GeneticAlgorithm CreateGpLawnMowerSample() {
41      GeneticAlgorithm ga = new GeneticAlgorithm();
42
43      #region Problem Configuration
44
45      var problem = new HeuristicLab.Problems.LawnMower.Problem();
46
47      #endregion
48      #region Algorithm Configuration
49
50      ga.Name = "Genetic Programming - Lawn Mower";
51      ga.Description = "A standard genetic programming algorithm to solve the lawn mower problem";
52      ga.Problem = problem;
53      SamplesUtils
54        .ConfigureGeneticAlgorithmParameters
55        <TournamentSelector, SubtreeCrossover, MultiSymbolicExpressionTreeArchitectureManipulator>(
56          ga, 1000, 1, 50, 0.25, 5);
57      var mutator = (MultiSymbolicExpressionTreeArchitectureManipulator)ga.Mutator;
58      mutator.Operators.SetItemCheckedState(mutator.Operators
59        .OfType<OnePointShaker>()
60        .Single(), false);
61
62      #endregion
63
64      return ga;
65    }
66  }
67}
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