#region License Information
/* HeuristicLab
* Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
*
* This file is part of HeuristicLab.
*
* HeuristicLab is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* HeuristicLab is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with HeuristicLab. If not, see .
*/
#endregion
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
namespace HeuristicLab.Optimization {
[StorableClass]
public abstract class MultiObjectiveBasicProblem : BasicProblem, IMultiObjectiveHeuristicOptimizationProblem, IMultiObjectiveProblemDefinition
where TEncoding : class, IEncoding {
[StorableConstructor]
protected MultiObjectiveBasicProblem(bool deserializing) : base(deserializing) { }
protected MultiObjectiveBasicProblem(MultiObjectiveBasicProblem original, Cloner cloner)
: base(original, cloner) {
ParameterizeOperators();
}
protected MultiObjectiveBasicProblem()
: base() {
Parameters.Add(new ValueParameter("Maximization", "Set to false if the problem should be minimized.", (BoolArray)new BoolArray(Maximization).AsReadOnly()));
Operators.Add(Evaluator);
Operators.Add(new MultiObjectiveAnalyzer());
ParameterizeOperators();
}
[StorableHook(HookType.AfterDeserialization)]
private void AfterDeserialization() {
ParameterizeOperators();
}
public abstract bool[] Maximization { get; }
public abstract double[] Evaluate(Individual individual, IRandom random);
public virtual void Analyze(Individual[] individuals, double[][] qualities, ResultCollection results, IRandom random) { }
protected override void OnOperatorsChanged() {
base.OnOperatorsChanged();
if (Encoding != null) {
PruneSingleObjectiveOperators(Encoding);
var multiEncoding = Encoding as MultiEncoding;
if (multiEncoding != null) {
foreach (var encoding in multiEncoding.Encodings.ToList()) {
PruneSingleObjectiveOperators(encoding);
}
}
}
}
private void PruneSingleObjectiveOperators(IEncoding encoding) {
if (encoding != null && encoding.Operators.Any(x => x is ISingleObjectiveOperator && !(x is IMultiObjectiveOperator)))
encoding.Operators = encoding.Operators.Where(x => !(x is ISingleObjectiveOperator) || x is IMultiObjectiveOperator).ToList();
}
protected override void OnEvaluatorChanged() {
base.OnEvaluatorChanged();
ParameterizeOperators();
}
private void ParameterizeOperators() {
foreach (var op in Operators.OfType())
op.EvaluateFunc = Evaluate;
foreach (var op in Operators.OfType())
op.AnalyzeAction = Analyze;
}
#region IMultiObjectiveHeuristicOptimizationProblem Members
IParameter IMultiObjectiveHeuristicOptimizationProblem.MaximizationParameter {
get { return Parameters["Maximization"]; }
}
IMultiObjectiveEvaluator IMultiObjectiveHeuristicOptimizationProblem.Evaluator {
get { return Evaluator; }
}
#endregion
}
}