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source: branches/2925_AutoDiffForDynamicalModels/HeuristicLab.Algorithms.OffspringSelectionGeneticAlgorithm/3.3/OffspringSelectionGeneticAlgorithmMainOperator.cs @ 16892

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Last change on this file since 16892 was 16892, checked in by gkronber, 5 years ago
#2925 merged r16661:16890 from trunk to branch
File size: 20.6 KB

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[3611]	1	#region License Information
	2	/* HeuristicLab
[16662]	3	* Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
[3611]	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
[16892]	22	using HEAL.Attic;
[4722]	23	using HeuristicLab.Common;
[3611]	24	using HeuristicLab.Core;
	25	using HeuristicLab.Data;
	26	using HeuristicLab.Operators;
	27	using HeuristicLab.Optimization.Operators;
	28	using HeuristicLab.Parameters;
	29	using HeuristicLab.Selection;
	30
	31	namespace HeuristicLab.Algorithms.OffspringSelectionGeneticAlgorithm {
	32	/// <summary>
	33	/// An operator which represents the main loop of an offspring selection genetic algorithm.
	34	/// </summary>
	35	[Item("OffspringSelectionGeneticAlgorithmMainOperator", "An operator that represents the core of an offspring selection genetic algorithm.")]
[16662]	36	[StorableType("43910E64-FC79-4AFF-8049-F427442E32BF")]
[3611]	37	public sealed class OffspringSelectionGeneticAlgorithmMainOperator : AlgorithmOperator {
	38	#region Parameter properties
	39	public ValueLookupParameter<IRandom> RandomParameter {
	40	get { return (ValueLookupParameter<IRandom>)Parameters["Random"]; }
	41	}
	42	public ValueLookupParameter<BoolValue> MaximizationParameter {
	43	get { return (ValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
	44	}
[3659]	45	public ScopeTreeLookupParameter<DoubleValue> QualityParameter {
	46	get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
[3611]	47	}
	48	public ValueLookupParameter<IOperator> SelectorParameter {
	49	get { return (ValueLookupParameter<IOperator>)Parameters["Selector"]; }
	50	}
	51	public ValueLookupParameter<IOperator> CrossoverParameter {
	52	get { return (ValueLookupParameter<IOperator>)Parameters["Crossover"]; }
	53	}
	54	public ValueLookupParameter<PercentValue> MutationProbabilityParameter {
	55	get { return (ValueLookupParameter<PercentValue>)Parameters["MutationProbability"]; }
	56	}
	57	public ValueLookupParameter<IOperator> MutatorParameter {
	58	get { return (ValueLookupParameter<IOperator>)Parameters["Mutator"]; }
	59	}
	60	public ValueLookupParameter<IOperator> EvaluatorParameter {
	61	get { return (ValueLookupParameter<IOperator>)Parameters["Evaluator"]; }
	62	}
	63	public LookupParameter<IntValue> EvaluatedSolutionsParameter {
	64	get { return (LookupParameter<IntValue>)Parameters["EvaluatedSolutions"]; }
	65	}
	66	public ValueLookupParameter<IntValue> ElitesParameter {
	67	get { return (ValueLookupParameter<IntValue>)Parameters["Elites"]; }
	68	}
[9569]	69	public IValueLookupParameter<BoolValue> ReevaluateElitesParameter {
	70	get { return (IValueLookupParameter<BoolValue>)Parameters["ReevaluateElites"]; }
	71	}
[3611]	72	public LookupParameter<DoubleValue> ComparisonFactorParameter {
	73	get { return (LookupParameter<DoubleValue>)Parameters["ComparisonFactor"]; }
	74	}
	75	public LookupParameter<DoubleValue> CurrentSuccessRatioParameter {
	76	get { return (LookupParameter<DoubleValue>)Parameters["CurrentSuccessRatio"]; }
	77	}
	78	public ValueLookupParameter<DoubleValue> SuccessRatioParameter {
	79	get { return (ValueLookupParameter<DoubleValue>)Parameters["SuccessRatio"]; }
	80	}
	81	public LookupParameter<DoubleValue> SelectionPressureParameter {
	82	get { return (LookupParameter<DoubleValue>)Parameters["SelectionPressure"]; }
	83	}
	84	public ValueLookupParameter<DoubleValue> MaximumSelectionPressureParameter {
	85	get { return (ValueLookupParameter<DoubleValue>)Parameters["MaximumSelectionPressure"]; }
	86	}
	87	public ValueLookupParameter<BoolValue> OffspringSelectionBeforeMutationParameter {
	88	get { return (ValueLookupParameter<BoolValue>)Parameters["OffspringSelectionBeforeMutation"]; }
	89	}
[10643]	90	public IValueLookupParameter<BoolValue> FillPopulationWithParentsParameter {
	91	get { return (IValueLookupParameter<BoolValue>)Parameters["FillPopulationWithParents"]; }
	92	}
[3611]	93	#endregion
	94
	95	[StorableConstructor]
[16662]	96	private OffspringSelectionGeneticAlgorithmMainOperator(StorableConstructorFlag _) : base(_) { }
[4722]	97	private OffspringSelectionGeneticAlgorithmMainOperator(OffspringSelectionGeneticAlgorithmMainOperator original, Cloner cloner)
	98	: base(original, cloner) {
	99	}
	100	public override IDeepCloneable Clone(Cloner cloner) {
	101	return new OffspringSelectionGeneticAlgorithmMainOperator(this, cloner);
	102	}
[3611]	103	public OffspringSelectionGeneticAlgorithmMainOperator()
	104	: base() {
	105	Initialize();
	106	}
	107
[9569]	108	[StorableHook(HookType.AfterDeserialization)]
	109	private void AfterDeserialization() {
[9592]	110	// BackwardsCompatibility3.3
[9591]	111	#region Backwards compatible code, remove with 3.4
[9569]	112	if (!Parameters.ContainsKey("ReevaluateElites")) {
	113	Parameters.Add(new ValueLookupParameter<BoolValue>("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)"));
	114	}
[10643]	115	if (!Parameters.ContainsKey("FillPopulationWithParents"))
	116	Parameters.Add(new ValueLookupParameter<BoolValue>("FillPopulationWithParents", "True if the population should be filled with parent individual or false if worse children should be used when the maximum selection pressure is exceeded."));
[9591]	117	#endregion
[9569]	118	}
	119
[3611]	120	private void Initialize() {
	121	#region Create parameters
	122	Parameters.Add(new ValueLookupParameter<IRandom>("Random", "A pseudo random number generator."));
	123	Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, otherwise false."));
[3659]	124	Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The value which represents the quality of a solution."));
[3611]	125	Parameters.Add(new ValueLookupParameter<IOperator>("Selector", "The operator used to select solutions for reproduction."));
	126	Parameters.Add(new ValueLookupParameter<IOperator>("Crossover", "The operator used to cross solutions."));
	127	Parameters.Add(new ValueLookupParameter<PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution."));
	128	Parameters.Add(new ValueLookupParameter<IOperator>("Mutator", "The operator used to mutate solutions."));
[5208]	129	Parameters.Add(new ValueLookupParameter<IOperator>("Evaluator", "The operator used to evaluate solutions. This operator is executed in parallel, if an engine is used which supports parallelization."));
[3611]	130	Parameters.Add(new LookupParameter<IntValue>("EvaluatedSolutions", "The number of evaluated solutions."));
	131	Parameters.Add(new ValueLookupParameter<IntValue>("Elites", "The numer of elite solutions which are kept in each generation."));
[9569]	132	Parameters.Add(new ValueLookupParameter<BoolValue>("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)"));
[3611]	133	Parameters.Add(new LookupParameter<DoubleValue>("ComparisonFactor", "The comparison factor is used to determine whether the offspring should be compared to the better parent, the worse parent or a quality value linearly interpolated between them. It is in the range [0;1]."));
	134	Parameters.Add(new LookupParameter<DoubleValue>("CurrentSuccessRatio", "The current success ratio."));
	135	Parameters.Add(new ValueLookupParameter<DoubleValue>("SuccessRatio", "The ratio of successful to total children that should be achieved."));
	136	Parameters.Add(new LookupParameter<DoubleValue>("SelectionPressure", "The actual selection pressure."));
	137	Parameters.Add(new ValueLookupParameter<DoubleValue>("MaximumSelectionPressure", "The maximum selection pressure that terminates the algorithm."));
	138	Parameters.Add(new ValueLookupParameter<BoolValue>("OffspringSelectionBeforeMutation", "True if the offspring selection step should be applied before mutation, false if it should be applied after mutation."));
[10643]	139	Parameters.Add(new ValueLookupParameter<BoolValue>("FillPopulationWithParents", "True if the population should be filled with parent individual or false if worse children should be used when the maximum selection pressure is exceeded."));
[3611]	140	#endregion
	141
	142	#region Create operators
	143	Placeholder selector = new Placeholder();
	144	SubScopesProcessor subScopesProcessor1 = new SubScopesProcessor();
	145	ChildrenCreator childrenCreator = new ChildrenCreator();
	146	ConditionalBranch osBeforeMutationBranch = new ConditionalBranch();
[5208]	147	UniformSubScopesProcessor uniformSubScopesProcessor1 = new UniformSubScopesProcessor();
	148	Placeholder crossover1 = new Placeholder();
	149	UniformSubScopesProcessor uniformSubScopesProcessor2 = new UniformSubScopesProcessor();
[3611]	150	Placeholder evaluator1 = new Placeholder();
[5356]	151	SubScopesCounter subScopesCounter1 = new SubScopesCounter();
[3611]	152	WeightedParentsQualityComparator qualityComparer1 = new WeightedParentsQualityComparator();
[5208]	153	SubScopesRemover subScopesRemover1 = new SubScopesRemover();
	154	UniformSubScopesProcessor uniformSubScopesProcessor3 = new UniformSubScopesProcessor();
[3611]	155	StochasticBranch mutationBranch1 = new StochasticBranch();
	156	Placeholder mutator1 = new Placeholder();
[5208]	157	VariableCreator variableCreator1 = new VariableCreator();
	158	VariableCreator variableCreator2 = new VariableCreator();
	159	ConditionalSelector conditionalSelector = new ConditionalSelector();
	160	SubScopesProcessor subScopesProcessor2 = new SubScopesProcessor();
	161	UniformSubScopesProcessor uniformSubScopesProcessor4 = new UniformSubScopesProcessor();
[3611]	162	Placeholder evaluator2 = new Placeholder();
[5356]	163	SubScopesCounter subScopesCounter2 = new SubScopesCounter();
[5208]	164	MergingReducer mergingReducer1 = new MergingReducer();
	165	UniformSubScopesProcessor uniformSubScopesProcessor5 = new UniformSubScopesProcessor();
	166	Placeholder crossover2 = new Placeholder();
[3611]	167	StochasticBranch mutationBranch2 = new StochasticBranch();
	168	Placeholder mutator2 = new Placeholder();
[5208]	169	UniformSubScopesProcessor uniformSubScopesProcessor6 = new UniformSubScopesProcessor();
[3611]	170	Placeholder evaluator3 = new Placeholder();
[5356]	171	SubScopesCounter subScopesCounter3 = new SubScopesCounter();
[3611]	172	WeightedParentsQualityComparator qualityComparer2 = new WeightedParentsQualityComparator();
[5208]	173	SubScopesRemover subScopesRemover2 = new SubScopesRemover();
[3611]	174	OffspringSelector offspringSelector = new OffspringSelector();
[5208]	175	SubScopesProcessor subScopesProcessor3 = new SubScopesProcessor();
[3713]	176	BestSelector bestSelector = new BestSelector();
	177	WorstSelector worstSelector = new WorstSelector();
[3611]	178	RightReducer rightReducer = new RightReducer();
[3699]	179	LeftReducer leftReducer = new LeftReducer();
[5208]	180	MergingReducer mergingReducer2 = new MergingReducer();
[9569]	181	ConditionalBranch reevaluateElitesBranch = new ConditionalBranch();
	182	UniformSubScopesProcessor uniformSubScopesProcessor7 = new UniformSubScopesProcessor();
	183	Placeholder evaluator4 = new Placeholder();
	184	SubScopesCounter subScopesCounter4 = new SubScopesCounter();
[4068]	185
[3611]	186	selector.Name = "Selector (placeholder)";
	187	selector.OperatorParameter.ActualName = SelectorParameter.Name;
	188
	189	childrenCreator.ParentsPerChild = new IntValue(2);
	190
	191	osBeforeMutationBranch.Name = "Apply OS before mutation?";
	192	osBeforeMutationBranch.ConditionParameter.ActualName = OffspringSelectionBeforeMutationParameter.Name;
	193
[5208]	194	crossover1.Name = "Crossover (placeholder)";
	195	crossover1.OperatorParameter.ActualName = CrossoverParameter.Name;
	196
	197	uniformSubScopesProcessor2.Parallel.Value = true;
	198
[3611]	199	evaluator1.Name = "Evaluator (placeholder)";
	200	evaluator1.OperatorParameter.ActualName = EvaluatorParameter.Name;
	201
[5356]	202	subScopesCounter1.Name = "Increment EvaluatedSolutions";
	203	subScopesCounter1.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
[3611]	204
	205	qualityComparer1.ComparisonFactorParameter.ActualName = ComparisonFactorParameter.Name;
	206	qualityComparer1.LeftSideParameter.ActualName = QualityParameter.Name;
	207	qualityComparer1.MaximizationParameter.ActualName = MaximizationParameter.Name;
	208	qualityComparer1.RightSideParameter.ActualName = QualityParameter.Name;
	209	qualityComparer1.ResultParameter.ActualName = "SuccessfulOffspring";
	210
[5208]	211	subScopesRemover1.RemoveAllSubScopes = true;
	212
[3611]	213	mutationBranch1.ProbabilityParameter.ActualName = MutationProbabilityParameter.Name;
	214	mutationBranch1.RandomParameter.ActualName = RandomParameter.Name;
	215
	216	mutator1.Name = "Mutator (placeholder)";
	217	mutator1.OperatorParameter.ActualName = MutatorParameter.Name;
	218
[5208]	219	variableCreator1.Name = "MutatedOffspring = true";
[16892]	220	variableCreator1.CollectedValues.Add(new ValueParameter<BoolValue>("MutatedOffspring", null, new BoolValue(true)) { GetsCollected = false });
[5208]	221
	222	variableCreator2.Name = "MutatedOffspring = false";
[16892]	223	variableCreator2.CollectedValues.Add(new ValueParameter<BoolValue>("MutatedOffspring", null, new BoolValue(false)) { GetsCollected = false });
[5208]	224
	225	conditionalSelector.ConditionParameter.ActualName = "MutatedOffspring";
	226	conditionalSelector.ConditionParameter.Depth = 1;
	227	conditionalSelector.CopySelected.Value = false;
	228
	229	uniformSubScopesProcessor4.Parallel.Value = true;
	230
[3611]	231	evaluator2.Name = "Evaluator (placeholder)";
	232	evaluator2.OperatorParameter.ActualName = EvaluatorParameter.Name;
	233
[5356]	234	subScopesCounter2.Name = "Increment EvaluatedSolutions";
	235	subScopesCounter2.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
[3611]	236
[5208]	237	crossover2.Name = "Crossover (placeholder)";
	238	crossover2.OperatorParameter.ActualName = CrossoverParameter.Name;
	239
[3611]	240	mutationBranch2.ProbabilityParameter.ActualName = MutationProbabilityParameter.Name;
	241	mutationBranch2.RandomParameter.ActualName = RandomParameter.Name;
	242
	243	mutator2.Name = "Mutator (placeholder)";
	244	mutator2.OperatorParameter.ActualName = MutatorParameter.Name;
	245
[5208]	246	uniformSubScopesProcessor6.Parallel.Value = true;
	247
[3611]	248	evaluator3.Name = "Evaluator (placeholder)";
	249	evaluator3.OperatorParameter.ActualName = EvaluatorParameter.Name;
	250
[5356]	251	subScopesCounter3.Name = "Increment EvaluatedSolutions";
	252	subScopesCounter3.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
[3611]	253
	254	qualityComparer2.ComparisonFactorParameter.ActualName = ComparisonFactorParameter.Name;
	255	qualityComparer2.LeftSideParameter.ActualName = QualityParameter.Name;
	256	qualityComparer2.MaximizationParameter.ActualName = MaximizationParameter.Name;
	257	qualityComparer2.RightSideParameter.ActualName = QualityParameter.Name;
	258	qualityComparer2.ResultParameter.ActualName = "SuccessfulOffspring";
	259
[5208]	260	subScopesRemover2.RemoveAllSubScopes = true;
[3611]	261
	262	offspringSelector.CurrentSuccessRatioParameter.ActualName = CurrentSuccessRatioParameter.Name;
	263	offspringSelector.MaximumSelectionPressureParameter.ActualName = MaximumSelectionPressureParameter.Name;
	264	offspringSelector.SelectionPressureParameter.ActualName = SelectionPressureParameter.Name;
	265	offspringSelector.SuccessRatioParameter.ActualName = SuccessRatioParameter.Name;
[3740]	266	offspringSelector.OffspringPopulationParameter.ActualName = "OffspringPopulation";
	267	offspringSelector.OffspringPopulationWinnersParameter.ActualName = "OffspringPopulationWinners";
	268	offspringSelector.SuccessfulOffspringParameter.ActualName = "SuccessfulOffspring";
[10643]	269	offspringSelector.FillPopulationWithParentsParameter.ActualName = FillPopulationWithParentsParameter.Name;
[3611]	270
[3713]	271	bestSelector.CopySelected = new BoolValue(false);
	272	bestSelector.MaximizationParameter.ActualName = MaximizationParameter.Name;
	273	bestSelector.NumberOfSelectedSubScopesParameter.ActualName = ElitesParameter.Name;
	274	bestSelector.QualityParameter.ActualName = QualityParameter.Name;
[3699]	275
[3713]	276	worstSelector.CopySelected = new BoolValue(false);
	277	worstSelector.MaximizationParameter.ActualName = MaximizationParameter.Name;
	278	worstSelector.NumberOfSelectedSubScopesParameter.ActualName = ElitesParameter.Name;
	279	worstSelector.QualityParameter.ActualName = QualityParameter.Name;
[9569]	280
	281	reevaluateElitesBranch.ConditionParameter.ActualName = "ReevaluateElites";
	282	reevaluateElitesBranch.Name = "Reevaluate elites ?";
	283
	284	uniformSubScopesProcessor7.Parallel.Value = true;
	285
	286	evaluator4.Name = "Evaluator (placeholder)";
	287	evaluator4.OperatorParameter.ActualName = EvaluatorParameter.Name;
	288
	289	subScopesCounter4.Name = "Increment EvaluatedSolutions";
	290	subScopesCounter4.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
[3611]	291	#endregion
	292
	293	#region Create operator graph
	294	OperatorGraph.InitialOperator = selector;
	295	selector.Successor = subScopesProcessor1;
	296	subScopesProcessor1.Operators.Add(new EmptyOperator());
	297	subScopesProcessor1.Operators.Add(childrenCreator);
	298	subScopesProcessor1.Successor = offspringSelector;
[5208]	299	childrenCreator.Successor = osBeforeMutationBranch;
	300	osBeforeMutationBranch.TrueBranch = uniformSubScopesProcessor1;
	301	osBeforeMutationBranch.FalseBranch = uniformSubScopesProcessor5;
	302	osBeforeMutationBranch.Successor = null;
	303	uniformSubScopesProcessor1.Operator = crossover1;
	304	uniformSubScopesProcessor1.Successor = uniformSubScopesProcessor2;
	305	crossover1.Successor = null;
	306	uniformSubScopesProcessor2.Operator = evaluator1;
[5356]	307	uniformSubScopesProcessor2.Successor = subScopesCounter1;
	308	evaluator1.Successor = qualityComparer1;
[5208]	309	qualityComparer1.Successor = subScopesRemover1;
	310	subScopesRemover1.Successor = null;
[5356]	311	subScopesCounter1.Successor = uniformSubScopesProcessor3;
[5208]	312	uniformSubScopesProcessor3.Operator = mutationBranch1;
	313	uniformSubScopesProcessor3.Successor = conditionalSelector;
[3611]	314	mutationBranch1.FirstBranch = mutator1;
[5208]	315	mutationBranch1.SecondBranch = variableCreator2;
[3611]	316	mutationBranch1.Successor = null;
[5208]	317	mutator1.Successor = variableCreator1;
	318	variableCreator1.Successor = null;
	319	variableCreator2.Successor = null;
	320	conditionalSelector.Successor = subScopesProcessor2;
	321	subScopesProcessor2.Operators.Add(new EmptyOperator());
	322	subScopesProcessor2.Operators.Add(uniformSubScopesProcessor4);
	323	subScopesProcessor2.Successor = mergingReducer1;
	324	uniformSubScopesProcessor4.Operator = evaluator2;
[5356]	325	uniformSubScopesProcessor4.Successor = subScopesCounter2;
	326	evaluator2.Successor = null;
	327	subScopesCounter2.Successor = null;
[5208]	328	mergingReducer1.Successor = null;
	329	uniformSubScopesProcessor5.Operator = crossover2;
	330	uniformSubScopesProcessor5.Successor = uniformSubScopesProcessor6;
	331	crossover2.Successor = mutationBranch2;
[3611]	332	mutationBranch2.FirstBranch = mutator2;
	333	mutationBranch2.SecondBranch = null;
[5208]	334	mutationBranch2.Successor = null;
[3611]	335	mutator2.Successor = null;
[5208]	336	uniformSubScopesProcessor6.Operator = evaluator3;
[5356]	337	uniformSubScopesProcessor6.Successor = subScopesCounter3;
	338	evaluator3.Successor = qualityComparer2;
[5208]	339	qualityComparer2.Successor = subScopesRemover2;
	340	subScopesRemover2.Successor = null;
[5356]	341	subScopesCounter3.Successor = null;
[3611]	342	offspringSelector.OffspringCreator = selector;
[5208]	343	offspringSelector.Successor = subScopesProcessor3;
	344	subScopesProcessor3.Operators.Add(bestSelector);
	345	subScopesProcessor3.Operators.Add(worstSelector);
	346	subScopesProcessor3.Successor = mergingReducer2;
[3713]	347	bestSelector.Successor = rightReducer;
[9569]	348	rightReducer.Successor = reevaluateElitesBranch;
	349	reevaluateElitesBranch.TrueBranch = uniformSubScopesProcessor7;
	350	uniformSubScopesProcessor7.Operator = evaluator4;
	351	uniformSubScopesProcessor7.Successor = subScopesCounter4;
	352	subScopesCounter4.Successor = null;
	353	reevaluateElitesBranch.FalseBranch = null;
	354	reevaluateElitesBranch.Successor = null;
[3713]	355	worstSelector.Successor = leftReducer;
[3699]	356	leftReducer.Successor = null;
[5208]	357	mergingReducer2.Successor = null;
[3611]	358	#endregion
	359	}
[3715]	360
	361	public override IOperation Apply() {
	362	if (CrossoverParameter.ActualValue == null)
	363	return null;
	364	return base.Apply();
	365	}
[3611]	366	}
	367	}

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