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source: trunk/sources/HeuristicLab.Tests/HeuristicLab-3.3/SamplesTest.cs @ 11024

Last change on this file since 11024 was 11008, checked in by gkronber, 11 years ago

#2109 removed incorrect unit test attributes from a helper method
File size: 71.6 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2013 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;
23using System.IO;
24using System.Linq;
25using System.Threading;
26using HeuristicLab.Algorithms.DataAnalysis;
27using HeuristicLab.Algorithms.EvolutionStrategy;
28using HeuristicLab.Algorithms.GeneticAlgorithm;
29using HeuristicLab.Algorithms.LocalSearch;
30using HeuristicLab.Algorithms.OffspringSelectionGeneticAlgorithm;
31using HeuristicLab.Algorithms.ParticleSwarmOptimization;
32using HeuristicLab.Algorithms.RAPGA;
33using HeuristicLab.Algorithms.ScatterSearch;
34using HeuristicLab.Algorithms.SimulatedAnnealing;
35using HeuristicLab.Algorithms.TabuSearch;
36using HeuristicLab.Algorithms.VariableNeighborhoodSearch;
37using HeuristicLab.Data;
38using HeuristicLab.Encodings.BinaryVectorEncoding;
39using HeuristicLab.Encodings.IntegerVectorEncoding;
40using HeuristicLab.Encodings.PermutationEncoding;
41using HeuristicLab.Encodings.RealVectorEncoding;
42using HeuristicLab.Encodings.ScheduleEncoding.JobSequenceMatrix;
43using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
44using HeuristicLab.Optimization;
45using HeuristicLab.Optimization.Operators;
46using HeuristicLab.Persistence.Default.Xml;
47using HeuristicLab.Problems.ArtificialAnt;
48using HeuristicLab.Problems.DataAnalysis;
49using HeuristicLab.Problems.DataAnalysis.Symbolic;
50using HeuristicLab.Problems.DataAnalysis.Symbolic.Classification;
51using HeuristicLab.Problems.DataAnalysis.Symbolic.Regression;
52using HeuristicLab.Problems.Instances;
53using HeuristicLab.Problems.Instances.DataAnalysis;
54using HeuristicLab.Problems.Instances.TSPLIB;
55using HeuristicLab.Problems.Instances.VehicleRouting;
56using HeuristicLab.Problems.Knapsack;
57using HeuristicLab.Problems.Scheduling;
58using HeuristicLab.Problems.TestFunctions;
59using HeuristicLab.Problems.TravelingSalesman;
60using HeuristicLab.Problems.VehicleRouting;
61using HeuristicLab.Problems.VehicleRouting.Encodings.General;
62using HeuristicLab.Problems.VehicleRouting.Encodings.Potvin;
63using HeuristicLab.Problems.VehicleRouting.ProblemInstances;
64using HeuristicLab.Selection;
65using Microsoft.VisualStudio.TestTools.UnitTesting;
66using StdDevStrategyVectorCreator = HeuristicLab.Encodings.RealVectorEncoding.StdDevStrategyVectorCreator;
67using StdDevStrategyVectorCrossover = HeuristicLab.Encodings.RealVectorEncoding.StdDevStrategyVectorCrossover;
68using StdDevStrategyVectorManipulator = HeuristicLab.Encodings.RealVectorEncoding.StdDevStrategyVectorManipulator;
69
70
71namespace HeuristicLab.Tests {
72  [TestClass]
73  public class SamplesTest {
74    private const string samplesDirectory = @"Samples\";
75
76    [ClassInitialize]
77    public static void MyClassInitialize(TestContext testContext) {
78      if (!Directory.Exists(samplesDirectory))
79        Directory.CreateDirectory(samplesDirectory);
80    }
81
82    #region GA
83    #region TSP
84    [TestMethod]
85    [TestCategory("Samples.Create")]
86    [TestProperty("Time", "medium")]
87    public void CreateGaTspSampleTest() {
88      var ga = CreateGaTspSample();
89      XmlGenerator.Serialize(ga, @"Samples\GA_TSP.hl");
90    }
91    [TestMethod]
92    [TestCategory("Samples.Execute")]
93    [TestProperty("Time", "long")]
94    public void RunGaTspSampleTest() {
95      var ga = CreateGaTspSample();
96      ga.SetSeedRandomly.Value = false;
97      RunAlgorithm(ga);
98      Assert.AreEqual(12332, GetDoubleResult(ga, "BestQuality"));
99      Assert.AreEqual(13123.2, GetDoubleResult(ga, "CurrentAverageQuality"));
100      Assert.AreEqual(14538, GetDoubleResult(ga, "CurrentWorstQuality"));
101      Assert.AreEqual(99100, GetIntResult(ga, "EvaluatedSolutions"));
102    }
103
104    private GeneticAlgorithm CreateGaTspSample() {
105      GeneticAlgorithm ga = new GeneticAlgorithm();
106      #region Problem Configuration
107      var provider = new TSPLIBTSPInstanceProvider();
108      var instance = provider.GetDataDescriptors().Where(x => x.Name == "ch130").Single();
109      TravelingSalesmanProblem tspProblem = new TravelingSalesmanProblem();
110      tspProblem.Load(provider.LoadData(instance));
111      tspProblem.UseDistanceMatrix.Value = true;
112      #endregion
113      #region Algorithm Configuration
114      ga.Name = "Genetic Algorithm - TSP";
115      ga.Description = "A genetic algorithm which solves the \"ch130\" traveling salesman problem (imported from TSPLIB)";
116      ga.Problem = tspProblem;
117      ConfigureGeneticAlgorithmParameters<ProportionalSelector, OrderCrossover2, InversionManipulator>(
118        ga, 100, 1, 1000, 0.05);
119      #endregion
120      return ga;
121    }
122    #endregion
123    #region VRP
124    [TestMethod]
125    [TestCategory("Samples.Create")]
126    [TestProperty("Time", "medium")]
127    public void CreateGaVrpSampleTest() {
128      var ga = CreateGaVrpSample();
129      XmlGenerator.Serialize(ga, @"Samples\GA_VRP.hl");
130    }
131
132    [TestMethod]
133    [TestCategory("Samples.Execute")]
134    [TestProperty("Time", "long")]
135    public void RunGaVrpSampleTest() {
136      var ga = CreateGaVrpSample();
137      ga.SetSeedRandomly.Value = false;
138      RunAlgorithm(ga);
139      Assert.AreEqual(1828.9368669428338, GetDoubleResult(ga, "BestQuality"));
140      Assert.AreEqual(1830.1444308908331, GetDoubleResult(ga, "CurrentAverageQuality"));
141      Assert.AreEqual(1871.7128510304112, GetDoubleResult(ga, "CurrentWorstQuality"));
142      Assert.AreEqual(99100, GetIntResult(ga, "EvaluatedSolutions"));
143    }
144
145    private GeneticAlgorithm CreateGaVrpSample() {
146      GeneticAlgorithm ga = new GeneticAlgorithm();
147      #region Problem Configuration
148      VehicleRoutingProblem vrpProblem = new VehicleRoutingProblem();
149
150      SolomonFormatInstanceProvider instanceProvider = new SolomonInstanceProvider();
151      CVRPTWData data = instanceProvider.Import(@"Test Resources\C101.txt", @"Test Resources\C101.opt.txt") as CVRPTWData;
152      vrpProblem.Load(data);
153      vrpProblem.Name = "C101 VRP (imported from Solomon)";
154      vrpProblem.Description = "Represents a Vehicle Routing Problem.";
155      CVRPTWProblemInstance instance = vrpProblem.ProblemInstance as CVRPTWProblemInstance;
156      instance.DistanceFactor.Value = 1;
157      instance.FleetUsageFactor.Value = 100;
158      instance.OverloadPenalty.Value = 100;
159      instance.TardinessPenalty.Value = 100;
160      instance.TimeFactor.Value = 0;
161      vrpProblem.MaximizationParameter.Value.Value = false;
162      instance.UseDistanceMatrix.Value = true;
163      instance.Vehicles.Value = 25;
164      #endregion
165      #region Algorithm Configuration
166      ga.Name = "Genetic Algorithm - VRP";
167      ga.Description = "A genetic algorithm which solves the \"C101\" vehicle routing problem (imported from Solomon)";
168      ga.Problem = vrpProblem;
169      ConfigureGeneticAlgorithmParameters<TournamentSelector, MultiVRPSolutionCrossover, MultiVRPSolutionManipulator>(
170        ga, 100, 1, 1000, 0.05, 3);
171
172      var xOver = (MultiVRPSolutionCrossover)ga.Crossover;
173      foreach (var op in xOver.Operators) {
174        xOver.Operators.SetItemCheckedState(op, false);
175      }
176      xOver.Operators.SetItemCheckedState(xOver.Operators
177        .OfType<PotvinRouteBasedCrossover>()
178        .Single(), true);
179      xOver.Operators.SetItemCheckedState(xOver.Operators
180        .OfType<PotvinSequenceBasedCrossover>()
181        .Single(), true);
182
183      var manipulator = (MultiVRPSolutionManipulator)ga.Mutator;
184      foreach (var op in manipulator.Operators) {
185        manipulator.Operators.SetItemCheckedState(op, false);
186      }
187      manipulator.Operators.SetItemCheckedState(manipulator.Operators
188        .OfType<PotvinOneLevelExchangeMainpulator>()
189        .Single(), true);
190      manipulator.Operators.SetItemCheckedState(manipulator.Operators
191        .OfType<PotvinTwoLevelExchangeManipulator>()
192        .Single(), true);
193      #endregion
194      return ga;
195    }
196    #endregion
197    #region ArtificialAnt
198    [TestMethod]
199    [TestCategory("Samples.Create")]
200    [TestProperty("Time", "medium")]
201    public void CreateGpArtificialAntSampleTest() {
202      var ga = CreateGpArtificialAntSample();
203      XmlGenerator.Serialize(ga, @"Samples\SGP_SantaFe.hl");
204    }
205
206    [TestMethod]
207    [TestCategory("Samples.Execute")]
208    [TestProperty("Time", "long")]
209    public void RunGpArtificialAntSampleTest() {
210      var ga = CreateGpArtificialAntSample();
211      ga.SetSeedRandomly.Value = false;
212      RunAlgorithm(ga);
213      Assert.AreEqual(81, GetDoubleResult(ga, "BestQuality"));
214      Assert.AreEqual(48.19, GetDoubleResult(ga, "CurrentAverageQuality"));
215      Assert.AreEqual(0, GetDoubleResult(ga, "CurrentWorstQuality"));
216      Assert.AreEqual(50950, GetIntResult(ga, "EvaluatedSolutions"));
217    }
218
219    public GeneticAlgorithm CreateGpArtificialAntSample() {
220      GeneticAlgorithm ga = new GeneticAlgorithm();
221      #region Problem Configuration
222      ArtificialAntProblem antProblem = new ArtificialAntProblem();
223      antProblem.BestKnownQuality.Value = 89;
224      antProblem.MaxExpressionDepth.Value = 10;
225      antProblem.MaxExpressionLength.Value = 100;
226      antProblem.MaxFunctionArguments.Value = 3;
227      antProblem.MaxFunctionDefinitions.Value = 3;
228      antProblem.MaxTimeSteps.Value = 600;
229      #endregion
230      #region Algorithm Configuration
231      ga.Name = "Genetic Programming - Artificial Ant";
232      ga.Description = "A standard genetic programming algorithm to solve the artificial ant problem (Santa-Fe trail)";
233      ga.Problem = antProblem;
234      ConfigureGeneticAlgorithmParameters<TournamentSelector, SubtreeCrossover, MultiSymbolicExpressionTreeArchitectureManipulator>(
235        ga, 1000, 1, 50, 0.15, 5);
236      var mutator = (MultiSymbolicExpressionTreeArchitectureManipulator)ga.Mutator;
237      mutator.Operators.SetItemCheckedState(mutator.Operators
238        .OfType<FullTreeShaker>()
239        .Single(), false);
240      mutator.Operators.SetItemCheckedState(mutator.Operators
241        .OfType<OnePointShaker>()
242        .Single(), false);
243      mutator.Operators.SetItemCheckedState(mutator.Operators
244        .OfType<ArgumentDeleter>()
245        .Single(), false);
246      mutator.Operators.SetItemCheckedState(mutator.Operators
247        .OfType<SubroutineDeleter>()
248        .Single(), false);
249      #endregion
250      return ga;
251    }
252    #endregion
253    #region Symbolic Regression
254    [TestMethod]
255    [TestCategory("Samples.Create")]
256    [TestProperty("Time", "medium")]
257    public void CreateGpSymbolicRegressionSampleTest() {
258      var ga = CreateGpSymbolicRegressionSample();
259      XmlGenerator.Serialize(ga, @"Samples\SGP_SymbReg.hl");
260    }
261    [TestMethod]
262    [TestCategory("Samples.Execute")]
263    [TestProperty("Time", "long")]
264    public void RunGpSymbolicRegressionSampleTest() {
265      var ga = CreateGpSymbolicRegressionSample();
266      ga.SetSeedRandomly.Value = false;
267      RunAlgorithm(ga);
268      Assert.AreEqual(0.858344291534625, GetDoubleResult(ga, "BestQuality"), 1E-8);
269      Assert.AreEqual(0.56758466520692641, GetDoubleResult(ga, "CurrentAverageQuality"), 1E-8);
270      Assert.AreEqual(0, GetDoubleResult(ga, "CurrentWorstQuality"), 1E-8);
271      Assert.AreEqual(50950, GetIntResult(ga, "EvaluatedSolutions"));
272      var bestTrainingSolution = (IRegressionSolution)ga.Results["Best training solution"].Value;
273      Assert.AreEqual(0.85504801557844745, bestTrainingSolution.TrainingRSquared, 1E-8);
274      Assert.AreEqual(0.86259381948647817, bestTrainingSolution.TestRSquared, 1E-8);
275      var bestValidationSolution = (IRegressionSolution)ga.Results["Best validation solution"].Value;
276      Assert.AreEqual(0.84854338315539746, bestValidationSolution.TrainingRSquared, 1E-8);
277      Assert.AreEqual(0.8662813452656678, bestValidationSolution.TestRSquared, 1E-8);
278    }
279
280    private GeneticAlgorithm CreateGpSymbolicRegressionSample() {
281      GeneticAlgorithm ga = new GeneticAlgorithm();
282      #region Problem Configuration
283      SymbolicRegressionSingleObjectiveProblem symbRegProblem = new SymbolicRegressionSingleObjectiveProblem();
284      symbRegProblem.Name = "Tower Symbolic Regression Problem";
285      symbRegProblem.Description = "Tower Dataset (downloaded from: http://www.symbolicregression.com/?q=towerProblem)";
286      RegressionRealWorldInstanceProvider provider = new RegressionRealWorldInstanceProvider();
287      var instance = provider.GetDataDescriptors().Where(x => x.Name.Equals("Tower")).Single();
288      var towerProblemData = (RegressionProblemData)provider.LoadData(instance);
289      towerProblemData.TargetVariableParameter.Value = towerProblemData.TargetVariableParameter.ValidValues
290        .First(v => v.Value == "towerResponse");
291      towerProblemData.InputVariables.SetItemCheckedState(
292        towerProblemData.InputVariables.Single(x => x.Value == "x1"), true);
293      towerProblemData.InputVariables.SetItemCheckedState(
294        towerProblemData.InputVariables.Single(x => x.Value == "x7"), false);
295      towerProblemData.InputVariables.SetItemCheckedState(
296        towerProblemData.InputVariables.Single(x => x.Value == "x11"), false);
297      towerProblemData.InputVariables.SetItemCheckedState(
298        towerProblemData.InputVariables.Single(x => x.Value == "x16"), false);
299      towerProblemData.InputVariables.SetItemCheckedState(
300        towerProblemData.InputVariables.Single(x => x.Value == "x21"), false);
301      towerProblemData.InputVariables.SetItemCheckedState(
302        towerProblemData.InputVariables.Single(x => x.Value == "x25"), false);
303      towerProblemData.InputVariables.SetItemCheckedState(
304        towerProblemData.InputVariables.Single(x => x.Value == "towerResponse"), false);
305      towerProblemData.TrainingPartition.Start = 0;
306      towerProblemData.TrainingPartition.End = 3136;
307      towerProblemData.TestPartition.Start = 3136;
308      towerProblemData.TestPartition.End = 4999;
309      towerProblemData.Name = "Data imported from towerData.txt";
310      towerProblemData.Description = "Chemical concentration at top of distillation tower, dataset downloaded from: http://vanillamodeling.com/realproblems.html, best R² achieved with nu-SVR = 0.97";
311      symbRegProblem.ProblemData = towerProblemData;
312
313      // configure grammar
314      var grammar = new TypeCoherentExpressionGrammar();
315      grammar.ConfigureAsDefaultRegressionGrammar();
316      grammar.Symbols.OfType<VariableCondition>().Single().InitialFrequency = 0.0;
317      var varSymbol = grammar.Symbols.OfType<Variable>().Where(x => !(x is LaggedVariable)).Single();
318      varSymbol.WeightMu = 1.0;
319      varSymbol.WeightSigma = 1.0;
320      varSymbol.WeightManipulatorMu = 0.0;
321      varSymbol.WeightManipulatorSigma = 0.05;
322      varSymbol.MultiplicativeWeightManipulatorSigma = 0.03;
323      var constSymbol = grammar.Symbols.OfType<Constant>().Single();
324      constSymbol.MaxValue = 20;
325      constSymbol.MinValue = -20;
326      constSymbol.ManipulatorMu = 0.0;
327      constSymbol.ManipulatorSigma = 1;
328      constSymbol.MultiplicativeManipulatorSigma = 0.03;
329      symbRegProblem.SymbolicExpressionTreeGrammar = grammar;
330
331      // configure remaining problem parameters
332      symbRegProblem.BestKnownQuality.Value = 0.97;
333      symbRegProblem.FitnessCalculationPartition.Start = 0;
334      symbRegProblem.FitnessCalculationPartition.End = 2300;
335      symbRegProblem.ValidationPartition.Start = 2300;
336      symbRegProblem.ValidationPartition.End = 3136;
337      symbRegProblem.RelativeNumberOfEvaluatedSamples.Value = 1;
338      symbRegProblem.MaximumSymbolicExpressionTreeLength.Value = 150;
339      symbRegProblem.MaximumSymbolicExpressionTreeDepth.Value = 12;
340      symbRegProblem.MaximumFunctionDefinitions.Value = 0;
341      symbRegProblem.MaximumFunctionArguments.Value = 0;
342
343      symbRegProblem.EvaluatorParameter.Value = new SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator();
344      #endregion
345      #region Algorithm Configuration
346      ga.Problem = symbRegProblem;
347      ga.Name = "Genetic Programming - Symbolic Regression";
348      ga.Description = "A standard genetic programming algorithm to solve a symbolic regression problem (tower dataset)";
349      ConfigureGeneticAlgorithmParameters<TournamentSelector, SubtreeCrossover, MultiSymbolicExpressionTreeManipulator>(
350        ga, 1000, 1, 50, 0.15, 5);
351      var mutator = (MultiSymbolicExpressionTreeManipulator)ga.Mutator;
352      mutator.Operators.OfType<FullTreeShaker>().Single().ShakingFactor = 0.1;
353      mutator.Operators.OfType<OnePointShaker>().Single().ShakingFactor = 1.0;
354
355      ga.Analyzer.Operators.SetItemCheckedState(
356        ga.Analyzer.Operators
357        .OfType<SymbolicRegressionSingleObjectiveOverfittingAnalyzer>()
358        .Single(), false);
359      ga.Analyzer.Operators.SetItemCheckedState(
360        ga.Analyzer.Operators
361        .OfType<SymbolicDataAnalysisAlleleFrequencyAnalyzer>()
362        .First(), false);
363      #endregion
364      return ga;
365    }
366    #endregion
367    #region Symbolic Classification
368    [TestMethod]
369    [TestCategory("Samples.Create")]
370    [TestProperty("Time", "medium")]
371    public void CreateGpSymbolicClassificationSampleTest() {
372      var ga = CreateGpSymbolicClassificationSample();
373      XmlGenerator.Serialize(ga, @"Samples\SGP_SymbClass.hl");
374    }
375
376    [TestMethod]
377    [TestCategory("Samples.Execute")]
378    [TestProperty("Time", "long")]
379    public void RunGpSymbolicClassificationSampleTest() {
380      var ga = CreateGpSymbolicClassificationSample();
381      ga.SetSeedRandomly.Value = false;
382      RunAlgorithm(ga);
383      Assert.AreEqual(0.141880203907627, GetDoubleResult(ga, "BestQuality"), 1E-8);
384      Assert.AreEqual(4.3246992327753295, GetDoubleResult(ga, "CurrentAverageQuality"), 1E-8);
385      Assert.AreEqual(100.62175156249987, GetDoubleResult(ga, "CurrentWorstQuality"), 1E-8);
386      Assert.AreEqual(100900, GetIntResult(ga, "EvaluatedSolutions"));
387      var bestTrainingSolution = (IClassificationSolution)ga.Results["Best training solution"].Value;
388      Assert.AreEqual(0.80875, bestTrainingSolution.TrainingAccuracy, 1E-8);
389      Assert.AreEqual(0.795031055900621, bestTrainingSolution.TestAccuracy, 1E-8);
390      var bestValidationSolution = (IClassificationSolution)ga.Results["Best validation solution"].Value;
391      Assert.AreEqual(0.81375, bestValidationSolution.TrainingAccuracy, 1E-8);
392      Assert.AreEqual(0.788819875776398, bestValidationSolution.TestAccuracy, 1E-8);
393    }
394
395    private GeneticAlgorithm CreateGpSymbolicClassificationSample() {
396      GeneticAlgorithm ga = new GeneticAlgorithm();
397      #region Problem Configuration
398      SymbolicClassificationSingleObjectiveProblem symbClassProblem = new SymbolicClassificationSingleObjectiveProblem();
399      symbClassProblem.Name = "Mammography Classification Problem";
400      symbClassProblem.Description = "Mammography dataset imported from the UCI machine learning repository (http://archive.ics.uci.edu/ml/datasets/Mammographic+Mass)";
401      UCIInstanceProvider provider = new UCIInstanceProvider();
402      var instance = provider.GetDataDescriptors().Where(x => x.Name.Equals("Mammography, M. Elter, 2007")).Single();
403      var mammoData = (ClassificationProblemData)provider.LoadData(instance);
404      mammoData.TargetVariableParameter.Value = mammoData.TargetVariableParameter.ValidValues
405        .First(v => v.Value == "Severity");
406      mammoData.InputVariables.SetItemCheckedState(
407        mammoData.InputVariables.Single(x => x.Value == "BI-RADS"), false);
408      mammoData.InputVariables.SetItemCheckedState(
409        mammoData.InputVariables.Single(x => x.Value == "Age"), true);
410      mammoData.InputVariables.SetItemCheckedState(
411        mammoData.InputVariables.Single(x => x.Value == "Shape"), true);
412      mammoData.InputVariables.SetItemCheckedState(
413        mammoData.InputVariables.Single(x => x.Value == "Margin"), true);
414      mammoData.InputVariables.SetItemCheckedState(
415        mammoData.InputVariables.Single(x => x.Value == "Density"), true);
416      mammoData.InputVariables.SetItemCheckedState(
417        mammoData.InputVariables.Single(x => x.Value == "Severity"), false);
418      mammoData.TrainingPartition.Start = 0;
419      mammoData.TrainingPartition.End = 800;
420      mammoData.TestPartition.Start = 800;
421      mammoData.TestPartition.End = 961;
422      mammoData.Name = "Data imported from mammographic_masses.csv";
423      mammoData.Description = "Original dataset: http://archive.ics.uci.edu/ml/datasets/Mammographic+Mass, missing values have been replaced with median values.";
424      symbClassProblem.ProblemData = mammoData;
425
426      // configure grammar
427      var grammar = new TypeCoherentExpressionGrammar();
428      grammar.ConfigureAsDefaultClassificationGrammar();
429      grammar.Symbols.OfType<VariableCondition>().Single().Enabled = false;
430      var varSymbol = grammar.Symbols.OfType<Variable>().Where(x => !(x is LaggedVariable)).Single();
431      varSymbol.WeightMu = 1.0;
432      varSymbol.WeightSigma = 1.0;
433      varSymbol.WeightManipulatorMu = 0.0;
434      varSymbol.WeightManipulatorSigma = 0.05;
435      varSymbol.MultiplicativeWeightManipulatorSigma = 0.03;
436      var constSymbol = grammar.Symbols.OfType<Constant>().Single();
437      constSymbol.MaxValue = 20;
438      constSymbol.MinValue = -20;
439      constSymbol.ManipulatorMu = 0.0;
440      constSymbol.ManipulatorSigma = 1;
441      constSymbol.MultiplicativeManipulatorSigma = 0.03;
442      symbClassProblem.SymbolicExpressionTreeGrammar = grammar;
443
444      // configure remaining problem parameters
445      symbClassProblem.BestKnownQuality.Value = 0.0;
446      symbClassProblem.FitnessCalculationPartition.Start = 0;
447      symbClassProblem.FitnessCalculationPartition.End = 400;
448      symbClassProblem.ValidationPartition.Start = 400;
449      symbClassProblem.ValidationPartition.End = 800;
450      symbClassProblem.RelativeNumberOfEvaluatedSamples.Value = 1;
451      symbClassProblem.MaximumSymbolicExpressionTreeLength.Value = 100;
452      symbClassProblem.MaximumSymbolicExpressionTreeDepth.Value = 10;
453      symbClassProblem.MaximumFunctionDefinitions.Value = 0;
454      symbClassProblem.MaximumFunctionArguments.Value = 0;
455      symbClassProblem.EvaluatorParameter.Value = new SymbolicClassificationSingleObjectiveMeanSquaredErrorEvaluator();
456      #endregion
457      #region Algorithm Configuration
458      ga.Problem = symbClassProblem;
459      ga.Name = "Genetic Programming - Symbolic Classification";
460      ga.Description = "A standard genetic programming algorithm to solve a classification problem (Mammographic+Mass dataset)";
461      ConfigureGeneticAlgorithmParameters<TournamentSelector, SubtreeCrossover, MultiSymbolicExpressionTreeManipulator>(
462        ga, 1000, 1, 100, 0.15, 5
463        );
464
465      var mutator = (MultiSymbolicExpressionTreeManipulator)ga.Mutator;
466      mutator.Operators.OfType<FullTreeShaker>().Single().ShakingFactor = 0.1;
467      mutator.Operators.OfType<OnePointShaker>().Single().ShakingFactor = 1.0;
468
469      ga.Analyzer.Operators.SetItemCheckedState(
470        ga.Analyzer.Operators
471        .OfType<SymbolicClassificationSingleObjectiveOverfittingAnalyzer>()
472        .Single(), false);
473      ga.Analyzer.Operators.SetItemCheckedState(
474        ga.Analyzer.Operators
475        .OfType<SymbolicDataAnalysisAlleleFrequencyAnalyzer>()
476        .First(), false);
477      #endregion
478      return ga;
479    }
480    #endregion
481    #region LawnMower
482    [TestMethod]
483    [TestCategory("Samples.Execute")]
484    [TestProperty("Time", "long")]
485    public void RunGpLawnMowerSampleTest() {
486      var ga = CreateGpLawnMowerSample();
487      ga.SetSeedRandomly.Value = false;
488      RunAlgorithm(ga);
489    }
490
491    public GeneticAlgorithm CreateGpLawnMowerSample() {
492      GeneticAlgorithm ga = new GeneticAlgorithm();
493      #region Problem Configuration
494      var problem = new HeuristicLab.Problems.LawnMower.Problem();
495      #endregion
496      #region Algorithm Configuration
497      ga.Name = "Genetic Programming - Lawn Mower";
498      ga.Description = "A standard genetic programming algorithm to solve the lawn mower problem";
499      ga.Problem = problem;
500      ConfigureGeneticAlgorithmParameters<TournamentSelector, SubtreeCrossover, MultiSymbolicExpressionTreeArchitectureManipulator>(
501        ga, 1000, 1, 50, 0.25, 5);
502      var mutator = (MultiSymbolicExpressionTreeArchitectureManipulator)ga.Mutator;
503      mutator.Operators.SetItemCheckedState(mutator.Operators
504        .OfType<OnePointShaker>()
505        .Single(), false);
506      #endregion
507      return ga;
508    }
509    #endregion
510    #endregion
511
512    #region ES
513    #region Griewank
514    [TestMethod]
515    [TestCategory("Samples.Create")]
516    [TestProperty("Time", "medium")]
517    public void CreateEsGriewankSampleTest() {
518      var es = CreateEsGriewankSample();
519      XmlGenerator.Serialize(es, @"Samples\ES_Griewank.hl");
520    }
521    [TestMethod]
522    [TestCategory("Samples.Execute")]
523    [TestProperty("Time", "long")]
524    public void RunEsGriewankSampleTest() {
525      var es = CreateEsGriewankSample();
526      es.SetSeedRandomly.Value = false;
527      RunAlgorithm(es);
528      Assert.AreEqual(0, GetDoubleResult(es, "BestQuality"));
529      Assert.AreEqual(0, GetDoubleResult(es, "CurrentAverageQuality"));
530      Assert.AreEqual(0, GetDoubleResult(es, "CurrentWorstQuality"));
531      Assert.AreEqual(100020, GetIntResult(es, "EvaluatedSolutions"));
532    }
533
534    private EvolutionStrategy CreateEsGriewankSample() {
535      EvolutionStrategy es = new EvolutionStrategy();
536      #region Problem Configuration
537      SingleObjectiveTestFunctionProblem problem = new SingleObjectiveTestFunctionProblem();
538
539      problem.ProblemSize.Value = 10;
540      problem.EvaluatorParameter.Value = new GriewankEvaluator();
541      problem.SolutionCreatorParameter.Value = new UniformRandomRealVectorCreator();
542      problem.Maximization.Value = false;
543      problem.Bounds = new DoubleMatrix(new double[,] { { -600, 600 } });
544      problem.BestKnownQuality.Value = 0;
545      problem.BestKnownSolutionParameter.Value = new RealVector(10);
546      problem.Name = "Single Objective Test Function";
547      problem.Description = "Test function with real valued inputs and a single objective.";
548      #endregion
549      #region Algorithm Configuration
550      es.Name = "Evolution Strategy - Griewank";
551      es.Description = "An evolution strategy which solves the 10-dimensional Griewank test function";
552      es.Problem = problem;
553      ConfigureEvolutionStrategyParameters<AverageCrossover, NormalAllPositionsManipulator,
554        StdDevStrategyVectorCreator, StdDevStrategyVectorCrossover, StdDevStrategyVectorManipulator>(
555        es, 20, 500, 2, 200, false);
556
557      StdDevStrategyVectorCreator strategyCreator = (StdDevStrategyVectorCreator)es.StrategyParameterCreator;
558      strategyCreator.BoundsParameter.Value = new DoubleMatrix(new double[,] { { 1, 20 } });
559
560      StdDevStrategyVectorManipulator strategyManipulator = (StdDevStrategyVectorManipulator)es.StrategyParameterManipulator;
561      strategyManipulator.BoundsParameter.Value = new DoubleMatrix(new double[,] { { 1E-12, 30 } });
562      strategyManipulator.GeneralLearningRateParameter.Value = new DoubleValue(0.22360679774997896);
563      strategyManipulator.LearningRateParameter.Value = new DoubleValue(0.39763536438352531);
564      #endregion
565      return es;
566    }
567    #endregion
568    #endregion
569
570    #region Island GA
571    #region TSP
572    [TestMethod]
573    [TestCategory("Samples.Create")]
574    [TestProperty("Time", "medium")]
575    public void CreateIslandGaTspSampleTest() {
576      var ga = CreateIslandGaTspSample();
577      XmlGenerator.Serialize(ga, @"Samples\IslandGA_TSP.hl");
578    }
579    [TestMethod]
580    [TestCategory("Samples.Execute")]
581    [TestProperty("Time", "long")]
582    public void RunIslandGaTspSampleTest() {
583      var ga = CreateIslandGaTspSample();
584      ga.SetSeedRandomly.Value = false;
585      RunAlgorithm(ga);
586      Assert.AreEqual(9918, GetDoubleResult(ga, "BestQuality"));
587      Assert.AreEqual(10324.64, GetDoubleResult(ga, "CurrentAverageQuality"));
588      Assert.AreEqual(11823, GetDoubleResult(ga, "CurrentWorstQuality"));
589      Assert.AreEqual(495500, GetIntResult(ga, "EvaluatedSolutions"));
590    }
591
592    private IslandGeneticAlgorithm CreateIslandGaTspSample() {
593      IslandGeneticAlgorithm ga = new IslandGeneticAlgorithm();
594      #region Problem Configuration
595      var provider = new TSPLIBTSPInstanceProvider();
596      var instance = provider.GetDataDescriptors().Where(x => x.Name == "ch130").Single();
597      TravelingSalesmanProblem tspProblem = new TravelingSalesmanProblem();
598      tspProblem.Load(provider.LoadData(instance));
599      tspProblem.UseDistanceMatrix.Value = true;
600      #endregion
601      #region Algorithm Configuration
602      ga.Name = "Island Genetic Algorithm - TSP";
603      ga.Description = "An island genetic algorithm which solves the \"ch130\" traveling salesman problem (imported from TSPLIB)";
604      ga.Problem = tspProblem;
605      ConfigureIslandGeneticAlgorithmParameters<ProportionalSelector, OrderCrossover2, InversionManipulator,
606        UnidirectionalRingMigrator, BestSelector, WorstReplacer>(
607        ga, 100, 1, 1000, 0.05, 5, 50, 0.25);
608      #endregion
609      return ga;
610    }
611    #endregion
612    #endregion
613
614    #region LS
615    #region Knapsack
616    [TestMethod]
617    [TestCategory("Samples.Create")]
618    [TestProperty("Time", "medium")]
619    public void CreateLocalSearchKnapsackSampleTest() {
620      var ls = CreateLocalSearchKnapsackSample();
621      XmlGenerator.Serialize(ls, @"Samples\LS_Knapsack.hl");
622    }
623    [TestMethod]
624    [TestCategory("Samples.Execute")]
625    [TestProperty("Time", "medium")]
626    public void RunLocalSearchKnapsackSampleTest() {
627      var ls = CreateLocalSearchKnapsackSample();
628      ls.SetSeedRandomly.Value = false;
629      RunAlgorithm(ls);
630      Assert.AreEqual(345, GetDoubleResult(ls, "BestQuality"));
631      Assert.AreEqual(340.70731707317071, GetDoubleResult(ls, "CurrentAverageQuality"));
632      Assert.AreEqual(337, GetDoubleResult(ls, "CurrentWorstQuality"));
633      Assert.AreEqual(82000, GetIntResult(ls, "EvaluatedMoves"));
634    }
635
636    private LocalSearch CreateLocalSearchKnapsackSample() {
637      LocalSearch ls = new LocalSearch();
638      #region Problem Configuration
639      KnapsackProblem problem = new KnapsackProblem();
640      problem.BestKnownQuality = new DoubleValue(362);
641      problem.BestKnownSolution = new HeuristicLab.Encodings.BinaryVectorEncoding.BinaryVector(new bool[] {
642       true , false, false, true , true , true , true , true , false, true , true , true , true , true , true , false, true , false, true , true , false, true , true , false, true , false, true , true , true , false, true , true , false, true , true , false, true , false, true , true , true , true , true , true , true , true , true , true , true , true , true , false, true , false, false, true , true , false, true , true , true , true , true , true , true , true , false, true , false, true , true , true , true , false, true , true , true , true , true , true , true , true});
643      problem.EvaluatorParameter.Value = new KnapsackEvaluator();
644      problem.SolutionCreatorParameter.Value = new RandomBinaryVectorCreator();
645      problem.KnapsackCapacity.Value = 297;
646      problem.Maximization.Value = true;
647      problem.Penalty.Value = 1;
648      problem.Values = new IntArray(new int[] {
649  6, 1, 1, 6, 7, 8, 7, 4, 2, 5, 2, 6, 7, 8, 7, 1, 7, 1, 9, 4, 2, 6, 5,  3, 5, 3, 3, 6, 5, 2, 4, 9, 4, 5, 7, 1, 4, 3, 5, 5, 8, 3, 6, 7, 3, 9, 7, 7, 5, 5, 7, 1, 4, 4, 3, 9, 5, 1, 6, 2, 2, 6, 1, 6, 5, 4, 4, 7, 1,  8, 9, 9, 7, 4, 3, 8, 7, 5, 7, 4, 4, 5});
650      problem.Weights = new IntArray(new int[] {
651 1, 9, 3, 6, 5, 3, 8, 1, 7, 4, 2, 1, 2, 7, 9, 9, 8, 4, 9, 2, 4, 8, 3, 7, 5, 7, 5, 5, 1, 9, 8, 7, 8, 9, 1, 3, 3, 8, 8, 5, 1, 2, 4, 3, 6, 9, 4, 4, 9, 7, 4, 5, 1, 9, 7, 6, 7, 4, 7, 1, 2, 1, 2, 9, 8, 6, 8, 4, 7, 6, 7, 5, 3, 9, 4, 7, 4, 6, 1, 2, 5, 4});
652      problem.Name = "Knapsack Problem";
653      problem.Description = "Represents a Knapsack problem.";
654      #endregion
655      #region Algorithm Configuration
656      ls.Name = "Local Search - Knapsack";
657      ls.Description = "A local search algorithm that solves a randomly generated Knapsack problem";
658      ls.Problem = problem;
659      ls.MaximumIterations.Value = 1000;
660      ls.MoveEvaluator = ls.MoveEvaluatorParameter.ValidValues
661        .OfType<KnapsackOneBitflipMoveEvaluator>()
662        .Single();
663      ls.MoveGenerator = ls.MoveGeneratorParameter.ValidValues
664        .OfType<ExhaustiveOneBitflipMoveGenerator>()
665        .Single();
666      ls.MoveMaker = ls.MoveMakerParameter.ValidValues
667        .OfType<OneBitflipMoveMaker>()
668        .Single();
669      ls.SampleSize.Value = 100;
670      ls.Seed.Value = 0;
671      ls.SetSeedRandomly.Value = true;
672      #endregion
673      ls.Engine = new ParallelEngine.ParallelEngine();
674      return ls;
675    }
676    #endregion
677    #endregion
678
679    #region PSO
680    #region Schwefel
681    [TestMethod]
682    [TestCategory("Samples.Create")]
683    [TestProperty("Time", "medium")]
684    public void CreatePsoSchwefelSampleTest() {
685      var pso = CreatePsoSchwefelSample();
686      XmlGenerator.Serialize(pso, @"Samples\PSO_Schwefel.hl");
687    }
688    [TestMethod]
689    [TestCategory("Samples.Execute")]
690    [TestProperty("Time", "medium")]
691    public void RunPsoSchwefelSampleTest() {
692      var pso = CreatePsoSchwefelSample();
693      pso.SetSeedRandomly.Value = false;
694      RunAlgorithm(pso);
695      if (!Environment.Is64BitProcess) {
696        Assert.AreEqual(118.44027985932837, GetDoubleResult(pso, "BestQuality"));
697        Assert.AreEqual(140.71570105946438, GetDoubleResult(pso, "CurrentAverageQuality"));
698        Assert.AreEqual(220.956806502853, GetDoubleResult(pso, "CurrentWorstQuality"));
699        Assert.AreEqual(1000, GetIntResult(pso, "Iterations"));
700      } else {
701        Assert.AreEqual(118.43958282879345, GetDoubleResult(pso, "BestQuality"));
702        Assert.AreEqual(139.43946864779372, GetDoubleResult(pso, "CurrentAverageQuality"));
703        Assert.AreEqual(217.14654589055152, GetDoubleResult(pso, "CurrentWorstQuality"));
704        Assert.AreEqual(1000, GetIntResult(pso, "Iterations"));
705      }
706    }
707    private ParticleSwarmOptimization CreatePsoSchwefelSample() {
708      ParticleSwarmOptimization pso = new ParticleSwarmOptimization();
709      #region Problem Configuration
710      var problem = new SingleObjectiveTestFunctionProblem();
711      problem.BestKnownQuality.Value = 0.0;
712      problem.BestKnownSolutionParameter.Value = new RealVector(new double[] { 420.968746, 420.968746 });
713      problem.Bounds = new DoubleMatrix(new double[,] { { -500, 500 } });
714      problem.EvaluatorParameter.Value = new SchwefelEvaluator();
715      problem.Maximization.Value = false;
716      problem.ProblemSize.Value = 2;
717      problem.SolutionCreatorParameter.Value = new UniformRandomRealVectorCreator();
718      #endregion
719      #region Algorithm Configuration
720      pso.Name = "Particle Swarm Optimization - Schwefel";
721      pso.Description = "A particle swarm optimization algorithm which solves the 2-dimensional Schwefel test function (based on the description in Pedersen, M.E.H. (2010). PhD thesis. University of Southampton)";
722      pso.Problem = problem;
723      pso.Inertia.Value = 10;
724      pso.MaxIterations.Value = 1000;
725      pso.NeighborBestAttraction.Value = 0.5;
726      pso.PersonalBestAttraction.Value = -0.01;
727      pso.SwarmSize.Value = 50;
728
729      var inertiaUpdater = pso.InertiaUpdaterParameter.ValidValues
730        .OfType<ExponentialDiscreteDoubleValueModifier>()
731        .Single();
732      inertiaUpdater.StartValueParameter.Value = new DoubleValue(10);
733      inertiaUpdater.EndValueParameter.Value = new DoubleValue(1);
734      pso.InertiaUpdater = inertiaUpdater;
735
736      pso.ParticleCreator = pso.ParticleCreatorParameter.ValidValues
737        .OfType<RealVectorParticleCreator>()
738        .Single();
739      var swarmUpdater = pso.SwarmUpdaterParameter.ValidValues
740        .OfType<RealVectorSwarmUpdater>()
741        .Single();
742      swarmUpdater.VelocityBoundsIndexParameter.ActualName = "Iterations";
743      swarmUpdater.VelocityBoundsParameter.Value = new DoubleMatrix(new double[,] { { -10, 10 } });
744      swarmUpdater.VelocityBoundsStartValueParameter.Value = new DoubleValue(10.0);
745      swarmUpdater.VelocityBoundsEndValueParameter.Value = new DoubleValue(1.0);
746      swarmUpdater.VelocityBoundsScalingOperatorParameter.Value = swarmUpdater.VelocityBoundsScalingOperatorParameter.ValidValues
747        .OfType<ExponentialDiscreteDoubleValueModifier>()
748        .Single();
749
750      pso.TopologyInitializer = null;
751      pso.TopologyUpdater = null;
752      pso.SwarmUpdater = swarmUpdater;
753      pso.Seed.Value = 0;
754      pso.SetSeedRandomly.Value = true;
755      #endregion
756      pso.Engine = new ParallelEngine.ParallelEngine();
757      return pso;
758    }
759    #endregion
760    #endregion
761
762    #region SA
763    #region Rastrigin
764    [TestMethod]
765    [TestCategory("Samples.Create")]
766    [TestProperty("Time", "medium")]
767    public void CreateSimulatedAnnealingRastriginSampleTest() {
768      var sa = CreateSimulatedAnnealingRastriginSample();
769      XmlGenerator.Serialize(sa, @"Samples\SA_Rastrigin.hl");
770    }
771    [TestMethod]
772    [TestCategory("Samples.Execute")]
773    [TestProperty("Time", "medium")]
774    public void RunSimulatedAnnealingRastriginSampleTest() {
775      var sa = CreateSimulatedAnnealingRastriginSample();
776      sa.SetSeedRandomly.Value = false;
777      RunAlgorithm(sa);
778      Assert.AreEqual(0.00014039606034543795, GetDoubleResult(sa, "BestQuality"));
779      Assert.AreEqual(5000, GetIntResult(sa, "EvaluatedMoves"));
780    }
781    private SimulatedAnnealing CreateSimulatedAnnealingRastriginSample() {
782      SimulatedAnnealing sa = new SimulatedAnnealing();
783      #region Problem Configuration
784      var problem = new SingleObjectiveTestFunctionProblem();
785      problem.BestKnownQuality.Value = 0.0;
786      problem.BestKnownSolutionParameter.Value = new RealVector(new double[] { 0, 0 });
787      problem.Bounds = new DoubleMatrix(new double[,] { { -5.12, 5.12 } });
788      problem.EvaluatorParameter.Value = new RastriginEvaluator();
789      problem.Maximization.Value = false;
790      problem.ProblemSize.Value = 2;
791      problem.SolutionCreatorParameter.Value = new UniformRandomRealVectorCreator();
792      #endregion
793      #region Algorithm Configuration
794      sa.Name = "Simulated Annealing - Rastrigin";
795      sa.Description = "A simulated annealing algorithm that solves the 2-dimensional Rastrigin test function";
796      sa.Problem = problem;
797      var annealingOperator = sa.AnnealingOperatorParameter.ValidValues
798        .OfType<ExponentialDiscreteDoubleValueModifier>()
799        .Single();
800      annealingOperator.StartIndexParameter.Value = new IntValue(0);
801      sa.AnnealingOperator = annealingOperator;
802
803      sa.EndTemperature.Value = 1E-6;
804      sa.InnerIterations.Value = 50;
805      sa.MaximumIterations.Value = 100;
806      var moveEvaluator = sa.MoveEvaluatorParameter.ValidValues
807        .OfType<RastriginAdditiveMoveEvaluator>()
808        .Single();
809      moveEvaluator.A.Value = 10;
810      sa.MoveEvaluator = moveEvaluator;
811
812      var moveGenerator = sa.MoveGeneratorParameter.ValidValues
813        .OfType<StochasticNormalMultiMoveGenerator>()
814        .Single();
815      moveGenerator.SigmaParameter.Value = new DoubleValue(1);
816      sa.MoveGenerator = moveGenerator;
817
818      sa.MoveMaker = sa.MoveMakerParameter.ValidValues
819        .OfType<AdditiveMoveMaker>()
820        .Single();
821
822      sa.Seed.Value = 0;
823      sa.SetSeedRandomly.Value = true;
824      sa.StartTemperature.Value = 1;
825      #endregion
826      sa.Engine = new ParallelEngine.ParallelEngine();
827      return sa;
828    }
829    #endregion
830    #endregion
831
832    #region TS
833    #region TSP
834    [TestMethod]
835    [TestCategory("Samples.Create")]
836    [TestProperty("Time", "medium")]
837    public void CreateTabuSearchTspSampleTest() {
838      var ts = CreateTabuSearchTspSample();
839      XmlGenerator.Serialize(ts, @"Samples\TS_TSP.hl");
840    }
841    [TestMethod]
842    [TestCategory("Samples.Execute")]
843    [TestProperty("Time", "long")]
844    public void RunTabuSearchTspSampleTest() {
845      var ts = CreateTabuSearchTspSample();
846      ts.SetSeedRandomly.Value = false;
847      RunAlgorithm(ts);
848      Assert.AreEqual(6294, GetDoubleResult(ts, "BestQuality"));
849      Assert.AreEqual(7380.0386666666664, GetDoubleResult(ts, "CurrentAverageQuality"));
850      Assert.AreEqual(8328, GetDoubleResult(ts, "CurrentWorstQuality"));
851      Assert.AreEqual(750000, GetIntResult(ts, "EvaluatedMoves"));
852    }
853
854    private TabuSearch CreateTabuSearchTspSample() {
855      TabuSearch ts = new TabuSearch();
856      #region Problem Configuration
857      var provider = new TSPLIBTSPInstanceProvider();
858      var instance = provider.GetDataDescriptors().Where(x => x.Name == "ch130").Single();
859      TravelingSalesmanProblem tspProblem = new TravelingSalesmanProblem();
860      tspProblem.Load(provider.LoadData(instance));
861      tspProblem.UseDistanceMatrix.Value = true;
862      #endregion
863      #region Algorithm Configuration
864      ts.Name = "Tabu Search - TSP";
865      ts.Description = "A tabu search algorithm that solves the \"ch130\" TSP (imported from TSPLIB)";
866      ts.Problem = tspProblem;
867
868      ts.MaximumIterations.Value = 1000;
869      // move generator has to be set first
870      var moveGenerator = ts.MoveGeneratorParameter.ValidValues
871        .OfType<StochasticInversionMultiMoveGenerator>()
872        .Single();
873      ts.MoveGenerator = moveGenerator;
874      var moveEvaluator = ts.MoveEvaluatorParameter.ValidValues
875        .OfType<TSPInversionMoveRoundedEuclideanPathEvaluator>()
876        .Single();
877      ts.MoveEvaluator = moveEvaluator;
878      var moveMaker = ts.MoveMakerParameter.ValidValues
879        .OfType<InversionMoveMaker>()
880        .Single();
881      ts.MoveMaker = moveMaker;
882      ts.SampleSize.Value = 750;
883      ts.Seed.Value = 0;
884      ts.SetSeedRandomly.Value = true;
885
886      var tabuChecker = ts.TabuCheckerParameter.ValidValues
887        .OfType<InversionMoveSoftTabuCriterion>()
888        .Single();
889      tabuChecker.UseAspirationCriterion.Value = true;
890      ts.TabuChecker = tabuChecker;
891
892      var tabuMaker = ts.TabuMakerParameter.ValidValues
893        .OfType<InversionMoveTabuMaker>()
894        .Single();
895      ts.TabuMaker = tabuMaker;
896      ts.TabuTenure.Value = 60;
897
898      #endregion
899      ts.Engine = new ParallelEngine.ParallelEngine();
900      return ts;
901    }
902    #endregion
903
904    #region VRP
905    [TestMethod]
906    [TestCategory("Samples.Create")]
907    [TestProperty("Time", "medium")]
908    public void CreateTabuSearchVRPSampleTest() {
909      var vrp = CreateTabuSearchVrpSample();
910      XmlGenerator.Serialize(vrp, @"Samples\TS_VRP.hl");
911    }
912    [TestMethod]
913    [TestCategory("Samples.Execute")]
914    [TestProperty("Time", "long")]
915    public void RunTabuSearchVRPSampleTest() {
916      var vrp = CreateTabuSearchVrpSample();
917      vrp.SetSeedRandomly.Value = false;
918      RunAlgorithm(vrp);
919      Assert.AreEqual(1473, GetDoubleResult(vrp, "BestQuality"));
920      Assert.AreEqual(2102.1192622950812, GetDoubleResult(vrp, "CurrentAverageQuality"));
921      Assert.AreEqual(4006, GetDoubleResult(vrp, "CurrentWorstQuality"));
922      Assert.AreEqual(119072, GetIntResult(vrp, "EvaluatedMoves"));
923    }
924
925    private TabuSearch CreateTabuSearchVrpSample() {
926      TabuSearch ts = new TabuSearch();
927      #region Problem Configuration
928      var provider = new AugeratInstanceProvider();
929      var instance = provider.GetDataDescriptors().Where(x => x.Name == "A-n62-k8").Single();
930      VehicleRoutingProblem vrpProblem = new VehicleRoutingProblem();
931      vrpProblem.Load(provider.LoadData(instance));
932      #endregion
933      #region Algorithm Configuration
934      ts.Name = "Tabu Search - VRP";
935      ts.Description = "A tabu search algorithm that solves the \"A-n62-k8\" VRP (imported from Augerat)";
936      ts.Problem = vrpProblem;
937
938      ts.MaximumIterations.Value = 200;
939      // move generator has to be set first
940      var moveGenerator = ts.MoveGeneratorParameter.ValidValues
941        .OfType<PotvinCustomerRelocationExhaustiveMoveGenerator>()
942        .Single();
943      ts.MoveGenerator = moveGenerator;
944      var moveEvaluator = ts.MoveEvaluatorParameter.ValidValues
945        .OfType<PotvinCustomerRelocationMoveEvaluator>()
946        .Single();
947      ts.MoveEvaluator = moveEvaluator;
948      var moveMaker = ts.MoveMakerParameter.ValidValues
949        .OfType<PotvinCustomerRelocationMoveMaker>()
950        .Single();
951      ts.MoveMaker = moveMaker;
952      ts.SampleSize.Value = 1000;
953      ts.Seed.Value = 0;
954      ts.SetSeedRandomly.Value = true;
955
956      var tabuChecker = ts.TabuCheckerParameter.ValidValues
957        .OfType<PotvinCustomerRelocationMoveTabuCriterion>()
958        .Single();
959      tabuChecker.UseAspirationCriterion.Value = false;
960      ts.TabuChecker = tabuChecker;
961
962      var tabuMaker = ts.TabuMakerParameter.ValidValues
963        .OfType<PotvinCustomerRelocationMoveTabuMaker>()
964        .Single();
965      ts.TabuMaker = tabuMaker;
966      ts.TabuTenure.Value = 6;
967
968      #endregion
969      ts.Engine = new ParallelEngine.ParallelEngine();
970      return ts;
971    }
972    #endregion
973    #endregion
974
975    #region VNS
976    #region TSP
977    [TestMethod]
978    [TestCategory("Samples.Create")]
979    [TestProperty("Time", "medium")]
980    public void CreateVnsTspSampleTest() {
981      var vns = CreateVnsTspSample();
982      XmlGenerator.Serialize(vns, @"Samples\VNS_TSP.hl");
983    }
984    [TestMethod]
985    [TestCategory("Samples.Execute")]
986    [TestProperty("Time", "long")]
987    public void RunVnsTspSampleTest() {
988      var vns = CreateVnsTspSample();
989      vns.SetSeedRandomly = false;
990      RunAlgorithm(vns);
991      Assert.AreEqual(867, GetDoubleResult(vns, "BestQuality"));
992      Assert.AreEqual(867, GetDoubleResult(vns, "CurrentAverageQuality"));
993      Assert.AreEqual(867, GetDoubleResult(vns, "CurrentWorstQuality"));
994      Assert.AreEqual(12975173, GetIntResult(vns, "EvaluatedSolutions"));
995    }
996
997    private VariableNeighborhoodSearch CreateVnsTspSample() {
998      VariableNeighborhoodSearch vns = new VariableNeighborhoodSearch();
999      #region Problem Configuration
1000      TravelingSalesmanProblem tspProblem = new TravelingSalesmanProblem();
1001      tspProblem.BestKnownSolution = new Permutation(PermutationTypes.Absolute, new int[] {
1002117, 65, 73, 74, 75, 76, 82, 86, 87, 94, 100, 106, 115, 120, 124, 107, 101, 108, 109, 102, 97, 90, 96, 95, 88, 89, 84, 78, 69, 57, 68, 56, 44, 55, 45, 36, 46, 37, 38, 47, 48, 59, 49, 58, 70, 77, 83, 79, 50, 80, 85, 98, 103, 110, 116, 121, 125, 133, 132, 138, 139, 146, 147, 159, 168, 169, 175, 182, 188, 201, 213, 189, 214, 221, 230, 246, 262, 276, 284, 275, 274, 261, 245, 229, 220, 228, 243, 259, 273, 282, 272, 258, 242, 257, 293, 292, 302, 310, 319, 320, 327, 326, 333, 340, 346, 339, 345, 344, 337, 338, 332, 325, 318, 309, 301, 291, 271, 251, 270, 233, 250, 269, 268, 280, 290, 300, 415, 440, 416, 417, 441, 458, 479, 418, 419, 395, 420, 442, 421, 396, 397, 422, 423, 461, 481, 502, 460, 501, 459, 480, 500, 517, 531, 516, 530, 499, 478, 457, 439, 414, 413, 412, 438, 456, 477, 498, 515, 529, 538, 547, 558, 559, 560, 548, 539, 549, 561, 562, 551, 550, 532, 540, 533, 541, 518, 534, 542, 552, 553, 554, 555, 535, 543, 556, 544, 536, 522, 505, 521, 520, 504, 519, 503, 482, 462, 463, 464, 483, 443, 465, 484, 506, 485, 507, 508, 487, 467, 486, 466, 445, 428, 444, 424, 425, 426, 427, 398, 399, 400, 381, 382, 371, 372, 401, 429, 446, 430, 402, 383, 366, 356, 357, 352, 385, 384, 403, 431, 447, 469, 468, 488, 489, 490, 470, 471, 448, 432, 433, 404, 405, 386, 373, 374, 367, 376, 375, 387, 491, 509, 537, 510, 492, 472, 449, 388, 389, 406, 450, 407, 377, 368, 359, 354, 350, 335, 324, 330, 390, 434, 451, 473, 493, 511, 523, 545, 563, 565, 567, 570, 569, 578, 577, 576, 575, 574, 573, 572, 580, 584, 583, 582, 587, 586, 585, 581, 579, 571, 568, 566, 564, 557, 546, 527, 513, 526, 525, 524, 512, 495, 494, 474, 452, 436, 409, 435, 453, 475, 496, 514, 528, 497, 455, 476, 454, 437, 411, 410, 394, 393, 392, 380, 370, 379, 408, 391, 378, 369, 364, 365, 361, 355, 351, 343, 336, 331, 317, 299, 286, 287, 278, 263, 264, 265, 223, 202, 248, 266, 279, 288, 289, 281, 267, 249, 232, 224, 216, 215, 204, 192, 193, 194, 186, 179, 185, 203, 191, 190, 177, 171, 161, 128, 135, 140, 149, 162, 150, 163, 172, 178, 173, 164, 152, 151, 141, 153, 165, 154, 142, 155, 143, 137, 136, 130, 129, 118, 114, 113, 105, 119, 123, 131, 144, 156, 157, 145, 158, 166, 167, 174, 180, 181, 187, 195, 205, 217, 226, 236, 225, 234, 252, 235, 253, 254, 255, 238, 239, 240, 241, 256, 237, 206, 207, 208, 196, 197, 198, 209, 199, 200, 211, 212, 219, 210, 218, 227, 244, 260, 283, 294, 295, 303, 296, 311, 304, 297, 298, 305, 285, 306, 314, 329, 321, 313, 312, 328, 334, 341, 347, 348, 353, 358, 362, 363, 360, 349, 342, 322, 323, 315, 316, 308, 307, 277, 247, 231, 222, 184, 183, 176, 170, 160, 148, 134, 127, 126, 111, 104, 92, 91, 71, 60, 51, 52, 40, 32, 23, 21, 20, 18, 17, 16, 14, 13, 11, 10, 7, 6, 5, 2, 1, 0, 3, 4, 31, 39, 25, 30, 35, 34, 33, 43, 54, 42, 27, 28, 29, 9, 8, 12, 15, 19, 22, 24, 26, 41, 67, 66, 64, 63, 53, 62, 61, 72, 81, 93, 99, 112, 122,
1003      });
1004      tspProblem.Coordinates = new DoubleMatrix(new double[,] {
1005{48, 71}, {49, 71}, {50, 71}, {44, 70}, {45, 70}, {52, 70}, {53, 70}, {54, 70}, {41, 69}, {42, 69}, {55, 69}, {56, 69}, {40, 68}, {56, 68}, {57, 68}, {39, 67}, {57, 67}, {58, 67}, {59, 67}, {38, 66}, {59, 66}, {60, 66}, {37, 65}, {60, 65}, {36, 64}, {43, 64}, {35, 63}, {37, 63}, {41, 63}, {42, 63}, {43, 63}, {47, 63}, {61, 63}, {40, 62}, {41, 62}, {42, 62}, {43, 62}, {45, 62}, {46, 62}, {47, 62}, {62, 62}, {34, 61}, {38, 61}, {39, 61}, {42, 61}, {43, 61}, {44, 61}, {45, 61}, {46, 61}, {47, 61}, {52, 61}, {62, 61}, {63, 61}, {26, 60}, {38, 60}, {42, 60}, {43, 60}, {44, 60}, {46, 60}, {47, 60}, {63, 60}, {23, 59}, {24, 59}, {27, 59}, {29, 59}, {30, 59}, {31, 59}, {33, 59}, {42, 59}, {46, 59}, {47, 59}, {63, 59}, {21, 58}, {32, 58}, {33, 58}, {34, 58}, {35, 58}, {46, 58}, {47, 58}, {48, 58}, {53, 58}, {21, 57}, {35, 57}, {47, 57}, {48, 57}, {53, 57}, {36, 56}, {37, 56}, {46, 56}, {47, 56}, {48, 56}, {64, 56}, {65, 56}, {20, 55}, {38, 55}, {46, 55}, {47, 55}, {48, 55}, {52, 55}, {21, 54}, {40, 54}, {47, 54}, {48, 54}, {52, 54}, {65, 54}, {30, 53}, {41, 53}, {46, 53}, {47, 53}, {48, 53}, {52, 53}, {65, 53}, {21, 52}, {32, 52}, {33, 52}, {42, 52}, {51, 52}, {21, 51}, {33, 51}, {34, 51}, {43, 51}, {51, 51}, {21, 50}, {35, 50}, {44, 50}, {50, 50}, {66, 50}, {67, 50}, {21, 49}, {34, 49}, {36, 49}, {37, 49}, {46, 49}, {49, 49}, {67, 49}, {22, 48}, {36, 48}, {37, 48}, {46, 48}, {47, 48}, {22, 47}, {30, 47}, {34, 47}, {37, 47}, {38, 47}, {39, 47}, {47, 47}, {48, 47}, {67, 47}, {23, 46}, {28, 46}, {29, 46}, {30, 46}, {31, 46}, {32, 46}, {35, 46}, {37, 46}, {38, 46}, {39, 46}, {49, 46}, {67, 46}, {23, 45}, {28, 45}, {29, 45}, {31, 45}, {32, 45}, {40, 45}, {41, 45}, {49, 45}, {50, 45}, {68, 45}, {24, 44}, {29, 44}, {32, 44}, {41, 44}, {51, 44}, {68, 44}, {25, 43}, {30, 43}, {32, 43}, {42, 43}, {43, 43}, {51, 43}, {68, 43}, {69, 43}, {31, 42}, {32, 42}, {43, 42}, {52, 42}, {55, 42}, {26, 41}, {27, 41}, {31, 41}, {32, 41}, {33, 41}, {44, 41}, {45, 41}, {46, 41}, {47, 41}, {48, 41}, {49, 41}, {53, 41}, {25, 40}, {27, 40}, {32, 40}, {43, 40}, {44, 40}, {45, 40}, {46, 40}, {48, 40}, {49, 40}, {50, 40}, {51, 40}, {53, 40}, {56, 40}, {32, 39}, {33, 39}, {43, 39}, {50, 39}, {51, 39}, {54, 39}, {56, 39}, {69, 39}, {24, 38}, {32, 38}, {41, 38}, {42, 38}, {51, 38}, {52, 38}, {54, 38}, {57, 38}, {69, 38}, {31, 37}, {32, 37}, {40, 37}, {41, 37}, {42, 37}, {43, 37}, {44, 37}, {45, 37}, {46, 37}, {47, 37}, {48, 37}, {51, 37}, {52, 37}, {55, 37}, {57, 37}, {69, 37}, {24, 36}, {31, 36}, {32, 36}, {39, 36}, {40, 36}, {41, 36}, {42, 36}, {43, 36}, {45, 36}, {48, 36}, {49, 36}, {51, 36}, {53, 36}, {55, 36}, {58, 36}, {22, 35}, {23, 35}, {24, 35}, {25, 35}, {30, 35}, {31, 35}, {32, 35}, {39, 35}, {41, 35}, {49, 35}, {51, 35}, {55, 35}, {56, 35}, {58, 35}, {71, 35}, {20, 34}, {27, 34}, {30, 34}, {31, 34}, {51, 34}, {53, 34}, {57, 34}, {60, 34}, {18, 33}, {19, 33}, {29, 33}, {30, 33}, {31, 33}, {45, 33}, {46, 33}, {47, 33}, {52, 33}, {53, 33}, {55, 33}, {57, 33}, {58, 33}, {17, 32}, {30, 32}, {44, 32}, {47, 32}, {54, 32}, {57, 32}, {59, 32}, {61, 32}, {71, 32}, {72, 32}, {43, 31}, {47, 31}, {56, 31}, {58, 31}, {59, 31}, {61, 31}, {72, 31}, {74, 31}, {16, 30}, {43, 30}, {46, 30}, {47, 30}, {59, 30}, {63, 30}, {71, 30}, {75, 30}, {43, 29}, {46, 29}, {47, 29}, {59, 29}, {60, 29}, {75, 29}, {15, 28}, {43, 28}, {46, 28}, {61, 28}, {76, 28}, {15, 27}, {43, 27}, {44, 27}, {45, 27}, {46, 27}, {60, 27}, {62, 27}, {15, 26}, {43, 26}, {44, 26}, {46, 26}, {59, 26}, {60, 26}, {64, 26}, {77, 26}, {15, 25}, {58, 25}, {61, 25}, {77, 25}, {15, 24}, {53, 24}, {55, 24}, {61, 24}, {77, 24}, {62, 23}, {16, 22}, {61, 22}, {62, 22}, {15, 21}, {16, 21}, {52, 21}, {63, 21}, {77, 21}, {16, 20}, {17, 20}, {46, 20}, {47, 20}, {60, 20}, {62, 20}, {63, 20}, {65, 20}, {76, 20}, {15, 19}, {17, 19}, {18, 19}, {44, 19}, {45, 19}, {48, 19}, {53, 19}, {56, 19}, {60, 19}, {62, 19}, {67, 19}, {68, 19}, {76, 19}, {15, 18}, {18, 18}, {19, 18}, {20, 18}, {32, 18}, {33, 18}, {34, 18}, {41, 18}, {42, 18}, {43, 18}, {46, 18}, {48, 18}, {53, 18}, {59, 18}, {60, 18}, {69, 18}, {75, 18}, {16, 17}, {17, 17}, {20, 17}, {21, 17}, {22, 17}, {23, 17}, {24, 17}, {26, 17}, {28, 17}, {29, 17}, {30, 17}, {31, 17}, {32, 17}, {34, 17}, {35, 17}, {36, 17}, {37, 17}, {38, 17}, {39, 17}, {40, 17}, {44, 17}, {46, 17}, {48, 17}, {53, 17}, {56, 17}, {58, 17}, {75, 17}, {17, 16}, {18, 16}, {20, 16}, {24, 16}, {26, 16}, {27, 16}, {29, 16}, {33, 16}, {41, 16}, {42, 16}, {44, 16}, {47, 16}, {52, 16}, {57, 16}, {70, 16}, {73, 16}, {74, 16}, {17, 15}, {18, 15}, {20, 15}, {22, 15}, {24, 15}, {27, 15}, {29, 15}, {31, 15}, {33, 15}, {35, 15}, {36, 15}, {38, 15}, {39, 15}, {42, 15}, {45, 15}, {47, 15}, {52, 15}, {53, 15}, {55, 15}, {56, 15}, {70, 15}, {73, 15}, {17, 14}, {19, 14}, {21, 14}, {24, 14}, {26, 14}, {29, 14}, {31, 14}, {34, 14}, {37, 14}, {40, 14}, {42, 14}, {44, 14}, {46, 14}, {47, 14}, {53, 14}, {54, 14}, {55, 14}, {62, 14}, {70, 14}, {72, 14}, {17, 13}, {19, 13}, {21, 13}, {23, 13}, {25, 13}, {27, 13}, {30, 13}, {32, 13}, {34, 13}, {36, 13}, {38, 13}, {41, 13}, {43, 13}, {44, 13}, {45, 13}, {60, 13}, {70, 13}, {71, 13}, {18, 12}, {21, 12}, {23, 12}, {26, 12}, {28, 12}, {31, 12}, {34, 12}, {37, 12}, {39, 12}, {41, 12}, {42, 12}, {70, 12}, {18, 11}, {19, 11}, {20, 11}, {21, 11}, {24, 11}, {25, 11}, {27, 11}, {29, 11}, {31, 11}, {33, 11}, {35, 11}, {38, 11}, {41, 11}, {59, 11}, {26, 10}, {29, 10}, {32, 10}, {34, 10}, {36, 10}, {39, 10}, {40, 10}, {69, 10}, {21, 9}, {26, 9}, {28, 9}, {30, 9}, {32, 9}, {33, 9}, {35, 9}, {36, 9}, {37, 9}, {38, 9}, {39, 9}, {22, 8}, {27, 8}, {28, 8}, {29, 8}, {30, 8}, {31, 8}, {68, 8}, {23, 7}, {66, 7}, {24, 6}, {65, 6}, {25, 5}, {62, 5}, {63, 5}, {26, 4}, {55, 4}, {56, 4}, {57, 4}, {58, 4}, {59, 4}, {60, 4}, {61, 4}, {28, 3}, {53, 3}, {29, 2}, {50, 2}, {51, 2}, {52, 2}, {31, 1}, {32, 1}, {48, 1}
1006      });
1007      tspProblem.BestKnownQuality = new DoubleValue(867);
1008
1009      tspProblem.EvaluatorParameter.Value = new TSPRoundedEuclideanPathEvaluator();
1010      tspProblem.SolutionCreatorParameter.Value = new RandomPermutationCreator();
1011      tspProblem.UseDistanceMatrix.Value = true;
1012      tspProblem.Name = "Funny TSP";
1013      tspProblem.Description = "Represents a symmetric Traveling Salesman Problem.";
1014      #endregion
1015      #region Algorithm Configuration
1016      vns.Name = "Variable Neighborhood Search - TSP";
1017      vns.Description = "A variable neighborhood search algorithm which solves a funny TSP instance";
1018      vns.Problem = tspProblem;
1019
1020      var localImprovement = vns.LocalImprovementParameter.ValidValues
1021        .OfType<LocalSearchImprovementOperator>()
1022        .Single();
1023      // move generator has to be set first
1024      localImprovement.MoveGenerator = localImprovement.MoveGeneratorParameter.ValidValues
1025        .OfType<StochasticInversionMultiMoveGenerator>()
1026        .Single();
1027      localImprovement.MoveEvaluator = localImprovement.MoveEvaluatorParameter.ValidValues
1028        .OfType<TSPInversionMoveRoundedEuclideanPathEvaluator>()
1029        .Single();
1030      localImprovement.MoveMaker = localImprovement.MoveMakerParameter.ValidValues
1031        .OfType<InversionMoveMaker>()
1032        .Single();
1033      localImprovement.SampleSizeParameter.Value = new IntValue(500);
1034      vns.LocalImprovement = localImprovement;
1035
1036      vns.LocalImprovementMaximumIterations = 150;
1037      vns.MaximumIterations = 25;
1038      vns.Seed = 0;
1039      vns.SetSeedRandomly = true;
1040      var shakingOperator = vns.ShakingOperatorParameter.ValidValues
1041        .OfType<PermutationShakingOperator>()
1042        .Single();
1043      shakingOperator.Operators.SetItemCheckedState(shakingOperator.Operators
1044        .OfType<Swap2Manipulator>()
1045        .Single(), false);
1046      shakingOperator.Operators.SetItemCheckedState(shakingOperator.Operators
1047        .OfType<Swap3Manipulator>()
1048        .Single(), false);
1049      vns.ShakingOperator = shakingOperator;
1050      #endregion
1051      vns.Engine = new ParallelEngine.ParallelEngine();
1052      return vns;
1053    }
1054    #endregion
1055    #endregion
1056
1057    #region Gaussian Process Regression
1058    [TestMethod]
1059    [TestCategory("Samples.Create")]
1060    [TestProperty("Time", "medium")]
1061    public void CreateGaussianProcessRegressionSampleTest() {
1062      var gpr = CreateGaussianProcessRegressionSample();
1063      XmlGenerator.Serialize(gpr, @"Samples\GPR.hl");
1064    }
1065    [TestMethod]
1066    [TestCategory("Samples.Execute")]
1067    [TestProperty("Time", "long")]
1068    public void RunGaussianProcessRegressionSample() {
1069      var gpr = CreateGaussianProcessRegressionSample();
1070      gpr.SetSeedRandomly = false;
1071      gpr.Seed = 1618551877;
1072      RunAlgorithm(gpr);
1073      Assert.AreEqual(-940.48768748097029, GetDoubleResult(gpr, "NegativeLogLikelihood"));
1074      Assert.AreEqual(0.99561947047986976, GetDoubleResult(gpr, "Training R²"));
1075    }
1076
1077    private GaussianProcessRegression CreateGaussianProcessRegressionSample() {
1078      var gpr = new GaussianProcessRegression();
1079      var provider = new VariousInstanceProvider();
1080      var instance = provider.GetDataDescriptors().Where(x => x.Name.Contains("Spatial co-evolution")).Single();
1081      var regProblem = new RegressionProblem();
1082      regProblem.Load(provider.LoadData(instance));
1083      #region Algorithm Configuration
1084      gpr.Name = "Gaussian Process Regression";
1085      gpr.Description = "A Gaussian process regression algorithm which solves the spatial co-evolution benchmark problem";
1086      gpr.Problem = regProblem;
1087
1088      gpr.CovarianceFunction = new CovarianceSquaredExponentialIso();
1089      gpr.MeanFunction = new MeanConst();
1090      gpr.MinimizationIterations = 20;
1091      gpr.Seed = 0;
1092      gpr.SetSeedRandomly = true;
1093      #endregion
1094      gpr.Engine = new ParallelEngine.ParallelEngine();
1095      return gpr;
1096    }
1097    #endregion
1098
1099    #region Scatter Search
1100    #region VRP
1101    [TestMethod]
1102    [TestCategory("Samples.Create")]
1103    [TestProperty("Time", "medium")]
1104    public void CreateScatterSearchVRPSampleTest() {
1105      var ss = CreateScatterSearchVRPSample();
1106      XmlGenerator.Serialize(ss, @"Samples\SS_VRP.hl");
1107    }
1108
1109    [TestMethod]
1110    [TestCategory("Samples.Execute")]
1111    [TestProperty("Time", "long")]
1112    public void RunScatterSearchVRPSampleTest() {
1113      var ss = CreateScatterSearchVRPSample();
1114      ss.SetSeedRandomly.Value = false;
1115      RunAlgorithm(ss);
1116      Assert.AreEqual(828.93686694283383, GetDoubleResult(ss, "BestQuality"));
1117      Assert.AreEqual(868.63623986983077, GetDoubleResult(ss, "CurrentAverageQuality"));
1118      Assert.AreEqual(1048.8333559209832, GetDoubleResult(ss, "CurrentWorstQuality"));
1119      Assert.AreEqual(262622, GetIntResult(ss, "EvaluatedSolutions"));
1120    }
1121
1122    private ScatterSearch CreateScatterSearchVRPSample() {
1123      #region Problem Configuration
1124      var provider = new SolomonInstanceProvider();
1125      var instance = provider.GetDataDescriptors().Single(x => x.Name == "C101");
1126      VehicleRoutingProblem vrpProblem = new VehicleRoutingProblem();
1127      vrpProblem.Load(provider.LoadData(instance));
1128      #endregion
1129
1130      #region Algorithm Configuration
1131      ScatterSearch ss = new ScatterSearch();
1132      ss.Engine = new SequentialEngine.SequentialEngine();
1133      ss.Name = "Scatter Search - VRP";
1134      ss.Description = "A scatter search algorithm which solves the \"C101\" vehicle routing problem (imported from Solomon)";
1135      ss.Problem = vrpProblem;
1136
1137      var improver = ss.Problem.Operators.OfType<VRPIntraRouteImprovementOperator>().First();
1138      improver.ImprovementAttemptsParameter.Value.Value = 15;
1139      improver.SampleSizeParameter.Value.Value = 10;
1140      ss.Improver = improver;
1141
1142      var pathRelinker = ss.Problem.Operators.OfType<VRPPathRelinker>().First();
1143      pathRelinker.IterationsParameter.Value.Value = 25;
1144      ss.PathRelinker = pathRelinker;
1145
1146      var similarityCalculator = ss.SimilarityCalculatorParameter.ValidValues.OfType<VRPSimilarityCalculator>().First();
1147      ss.SimilarityCalculator = similarityCalculator;
1148
1149      ss.MaximumIterations.Value = 2;
1150      ss.PopulationSize.Value = 20;
1151      ss.ReferenceSetSize.Value = 10;
1152      ss.Seed.Value = 0;
1153      return ss;
1154      #endregion
1155    }
1156    #endregion
1157    #endregion
1158
1159    #region RAPGA
1160    #region Scheduling
1161    [TestMethod]
1162    [TestCategory("Samples.Create")]
1163    [TestProperty("Time", "medium")]
1164    public void CreateRAPGASchedulingSampleTest() {
1165      var ss = CreateRAPGASchedulingSample();
1166      XmlGenerator.Serialize(ss, @"Samples\RAPGA_JSSP.hl");
1167    }
1168
1169    [TestMethod]
1170    [TestCategory("Samples.Execute")]
1171    [TestProperty("Time", "long")]
1172    public void RunRAPGASchedulingSampleTest() {
1173      var rapga = CreateRAPGASchedulingSample();
1174      rapga.SetSeedRandomly.Value = false;
1175      RunAlgorithm(rapga);
1176      Assert.AreEqual(988.00, GetDoubleResult(rapga, "BestQuality"));
1177      Assert.AreEqual(988.00, GetDoubleResult(rapga, "CurrentAverageQuality"));
1178      Assert.AreEqual(988.00, GetDoubleResult(rapga, "CurrentWorstQuality"));
1179      Assert.AreEqual(27100, GetIntResult(rapga, "EvaluatedSolutions"));
1180    }
1181
1182    private RAPGA CreateRAPGASchedulingSample() {
1183      #region Problem Configuration
1184      JobShopSchedulingProblem problem = new JobShopSchedulingProblem();
1185      #endregion
1186
1187      #region Algorithm Configuration
1188      RAPGA rapga = new RAPGA();
1189      rapga.Engine = new SequentialEngine.SequentialEngine();
1190      rapga.Name = "RAPGA - Job Shop Scheduling";
1191      rapga.Description = "A relevant alleles preserving genetic algorithm which solves a job shop scheduling problem";
1192      rapga.Problem = problem;
1193      rapga.Mutator = rapga.MutatorParameter.ValidValues.OfType<JSMSwapManipulator>().First();
1194      rapga.Seed.Value = 0;
1195      return rapga;
1196      #endregion
1197    }
1198    #endregion
1199    #endregion
1200
1201    #region grammatical evolution
1202    #region artificial ant
1203    [TestMethod]
1204    [TestCategory("Samples.Create")]
1205    [TestProperty("Time", "medium")]
1206    public void CreateGeArtificialAntSampleTest() {
1207      var geaa = CreateGeArtificialAntSample();
1208      XmlGenerator.Serialize(geaa, @"Samples\GE_ArtificialAnt.hl");
1209    }
1210
1211    [TestMethod]
1212    [TestCategory("Samples.Execute")]
1213    [TestProperty("Time", "long")]
1214    public void RunGeArtificalAntSampleTest() {
1215      var ga = CreateGeArtificialAntSample();
1216      ga.SetSeedRandomly.Value = false;
1217      RunAlgorithm(ga);
1218    }
1219
1220    public OffspringSelectionGeneticAlgorithm CreateGeArtificialAntSample() {
1221      OffspringSelectionGeneticAlgorithm ga = new OffspringSelectionGeneticAlgorithm();
1222      #region Problem Configuration
1223      var problem = new HeuristicLab.Problems.GrammaticalEvolution.GEArtificialAntProblem();
1224      #endregion
1225      #region Algorithm Configuration
1226      ga.Name = "Grammatical Evolution - Artificial Ant (SantaFe)";
1227      ga.Description = "Grammatical evolution algorithm for solving a artificial ant problem";
1228      ga.Problem = problem;
1229      ConfigureOsGeneticAlgorithmParameters<GenderSpecificSelector, Encodings.IntegerVectorEncoding.SinglePointCrossover, Encodings.IntegerVectorEncoding.UniformOnePositionManipulator>(
1230        ga, 200, 1, 50, 0.05, 200);
1231      #endregion
1232      return ga;
1233    }
1234    #endregion
1235
1236    #region symbolic regression
1237    #endregion
1238    [TestMethod]
1239    [TestCategory("Samples.Create")]
1240    [TestProperty("Time", "medium")]
1241    public void CreateGeSymbolicRegressionSampleTest() {
1242      var geSymbReg = CreateGeSymbolicRegressionSample();
1243      XmlGenerator.Serialize(geSymbReg, @"Samples\GE_SymbReg.hl");
1244    }
1245
1246    [TestMethod]
1247    [TestCategory("Samples.Execute")]
1248    [TestProperty("Time", "long")]
1249    public void RunGeSymbolicRegressionSampleTest() {
1250      var ga = CreateGeSymbolicRegressionSample();
1251      ga.SetSeedRandomly.Value = false;
1252      RunAlgorithm(ga);
1253    }
1254
1255    public OffspringSelectionGeneticAlgorithm CreateGeSymbolicRegressionSample() {
1256      var ga = new OffspringSelectionGeneticAlgorithm();
1257      #region Problem Configuration
1258      var problem = new HeuristicLab.Problems.GrammaticalEvolution.GESymbolicRegressionSingleObjectiveProblem();
1259
1260      #endregion
1261      #region Algorithm Configuration
1262      ga.Name = "Grammatical Evolution - Symbolic Regression (Poly-10)";
1263      ga.Description = "Grammatical evolution algorithm for solving a symbolic regression problem problem";
1264      ga.Problem = problem;
1265      problem.Load(new PolyTen().GenerateRegressionData());
1266
1267      // must occur after loading problem data because the grammar creates symbols for random constants once the data is loaded
1268      var consts = problem.SymbolicExpressionTreeGrammar.AllowedSymbols.OfType<Constant>().ToList();
1269      foreach (var c in consts) {
1270        problem.SymbolicExpressionTreeGrammar.RemoveSymbol(c);
1271      }
1272
1273      ConfigureOsGeneticAlgorithmParameters<GenderSpecificSelector, Encodings.IntegerVectorEncoding.SinglePointCrossover, Encodings.IntegerVectorEncoding.UniformOnePositionManipulator>(
1274        ga, 1000, 1, 50, 0.05, 200);
1275      #endregion
1276      return ga;
1277    }
1278    #endregion
1279
1280    #region Helpers
1281    private void ConfigureEvolutionStrategyParameters<R, M, SC, SR, SM>(EvolutionStrategy es, int popSize, int children, int parentsPerChild, int maxGens, bool plusSelection)
1282      where R : ICrossover
1283      where M : IManipulator
1284      where SC : IStrategyParameterCreator
1285      where SR : IStrategyParameterCrossover
1286      where SM : IStrategyParameterManipulator {
1287      es.PopulationSize.Value = popSize;
1288      es.Children.Value = children;
1289      es.ParentsPerChild.Value = parentsPerChild;
1290      es.MaximumGenerations.Value = maxGens;
1291      es.PlusSelection.Value = false;
1292
1293      es.Seed.Value = 0;
1294      es.SetSeedRandomly.Value = true;
1295
1296      es.Recombinator = es.RecombinatorParameter.ValidValues
1297        .OfType<R>()
1298        .Single();
1299
1300      es.Mutator = es.MutatorParameter.ValidValues
1301        .OfType<M>()
1302        .Single();
1303
1304      es.StrategyParameterCreator = es.StrategyParameterCreatorParameter.ValidValues
1305        .OfType<SC>()
1306        .Single();
1307      es.StrategyParameterCrossover = es.StrategyParameterCrossoverParameter.ValidValues
1308        .OfType<SR>()
1309        .Single();
1310      es.StrategyParameterManipulator = es.StrategyParameterManipulatorParameter.ValidValues
1311        .OfType<SM>()
1312        .Single();
1313      es.Engine = new ParallelEngine.ParallelEngine();
1314    }
1315
1316    private void ConfigureGeneticAlgorithmParameters<S, C, M>(GeneticAlgorithm ga, int popSize, int elites, int maxGens, double mutationRate, int tournGroupSize = 0)
1317      where S : ISelector
1318      where C : ICrossover
1319      where M : IManipulator {
1320      ga.Elites.Value = elites;
1321      ga.MaximumGenerations.Value = maxGens;
1322      ga.MutationProbability.Value = mutationRate;
1323      ga.PopulationSize.Value = popSize;
1324      ga.Seed.Value = 0;
1325      ga.SetSeedRandomly.Value = true;
1326      ga.Selector = ga.SelectorParameter.ValidValues
1327        .OfType<S>()
1328        .First();
1329
1330      ga.Crossover = ga.CrossoverParameter.ValidValues
1331        .OfType<C>()
1332        .First();
1333
1334      ga.Mutator = ga.MutatorParameter.ValidValues
1335        .OfType<M>()
1336        .First();
1337
1338      var tSelector = ga.Selector as TournamentSelector;
1339      if (tSelector != null) {
1340        tSelector.GroupSizeParameter.Value.Value = tournGroupSize;
1341      }
1342      ga.Engine = new ParallelEngine.ParallelEngine();
1343    }
1344
1345    private void ConfigureOsGeneticAlgorithmParameters<S, C, M>(OffspringSelectionGeneticAlgorithm ga, int popSize, int elites, int maxGens, double mutationRate=0.05, double maxSelPres=100, int tournGroupSize = 0)
1346      where S : ISelector
1347      where C : ICrossover
1348      where M : IManipulator {
1349      ga.Elites.Value = elites;
1350      ga.MaximumGenerations.Value = maxGens;
1351      ga.MutationProbability.Value = mutationRate;
1352      ga.PopulationSize.Value = popSize;
1353      ga.MaximumSelectionPressure.Value = maxSelPres;
1354      ga.Seed.Value = 0;
1355      ga.SetSeedRandomly.Value = true;
1356      ga.ComparisonFactorLowerBound.Value = 1;
1357      ga.ComparisonFactorUpperBound.Value = 1;
1358
1359      ga.Selector = ga.SelectorParameter.ValidValues
1360        .OfType<S>()
1361        .First();
1362
1363      ga.Crossover = ga.CrossoverParameter.ValidValues
1364        .OfType<C>()
1365        .First();
1366
1367      ga.Mutator = ga.MutatorParameter.ValidValues
1368        .OfType<M>()
1369        .First();
1370
1371      var tSelector = ga.Selector as TournamentSelector;
1372      if (tSelector != null) {
1373        tSelector.GroupSizeParameter.Value.Value = tournGroupSize;
1374      }
1375      ga.Engine = new ParallelEngine.ParallelEngine();
1376    }
1377
1378    private void ConfigureIslandGeneticAlgorithmParameters<S, C, M, Mi, MiS, MiR>(IslandGeneticAlgorithm ga, int popSize, int elites, int maxGens, double mutationRate, int numberOfIslands, int migrationInterval, double migrationRate)
1379      where S : ISelector
1380      where C : ICrossover
1381      where M : IManipulator
1382      where Mi : IMigrator
1383      where MiS : ISelector
1384      where MiR : IReplacer {
1385      ga.Elites.Value = elites;
1386      ga.MaximumGenerations.Value = maxGens;
1387      ga.MutationProbability.Value = mutationRate;
1388      ga.PopulationSize.Value = popSize;
1389      ga.NumberOfIslands.Value = numberOfIslands;
1390      ga.MigrationInterval.Value = migrationInterval;
1391      ga.MigrationRate.Value = migrationRate;
1392      ga.Seed.Value = 0;
1393      ga.SetSeedRandomly.Value = true;
1394      ga.Selector = ga.SelectorParameter.ValidValues
1395        .OfType<S>()
1396        .Single();
1397
1398      ga.Crossover = ga.CrossoverParameter.ValidValues
1399        .OfType<C>()
1400        .Single();
1401
1402      ga.Mutator = ga.MutatorParameter.ValidValues
1403        .OfType<M>()
1404        .Single();
1405      ga.Migrator = ga.MigratorParameter.ValidValues
1406        .OfType<Mi>()
1407        .Single();
1408      ga.EmigrantsSelector = ga.EmigrantsSelectorParameter.ValidValues
1409        .OfType<MiS>()
1410        .Single();
1411      ga.ImmigrationReplacer = ga.ImmigrationReplacerParameter.ValidValues
1412        .OfType<MiR>()
1413        .Single();
1414      ga.Engine = new ParallelEngine.ParallelEngine();
1415    }
1416
1417
1418    private void RunAlgorithm(IAlgorithm a) {
1419      var trigger = new EventWaitHandle(false, EventResetMode.ManualReset);
1420      Exception ex = null;
1421      a.Stopped += (src, e) => { trigger.Set(); };
1422      a.ExceptionOccurred += (src, e) => { ex = e.Value; trigger.Set(); };
1423      a.Prepare();
1424      a.Start();
1425      trigger.WaitOne();
1426
1427      Assert.AreEqual(ex, null);
1428    }
1429
1430    private double GetDoubleResult(IAlgorithm a, string resultName) {
1431      return ((DoubleValue)a.Results[resultName].Value).Value;
1432    }
1433    private int GetIntResult(IAlgorithm a, string resultName) {
1434      return ((IntValue)a.Results[resultName].Value).Value;
1435    }
1436    #endregion
1437  }
1438}
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