#region License Information
/* HeuristicLab
* Copyright (C) 2002-2014 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.Analysis;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
namespace HeuristicLab.Problems.Programmable {
[StorableClass]
public abstract class SingleObjectiveProgrammableProblem : ProgrammableProblem,
ISingleObjectiveProblemDefinition, ISingleObjectiveHeuristicOptimizationProblem
where TEncoding : class, IEncoding {
[StorableConstructor]
protected SingleObjectiveProgrammableProblem(bool deserializing) : base(deserializing) { }
protected SingleObjectiveProgrammableProblem(SingleObjectiveProgrammableProblem original, Cloner cloner)
: base(original, cloner) {
ParameterizeOperators();
}
protected SingleObjectiveProgrammableProblem()
: base() {
Parameters.Add(new FixedValueParameter("Maximization", "Set to false if the problem should be minimized.", new BoolValue(Maximization)));
Parameters.Add(new OptionalValueParameter("BestKnownQuality", "The quality of the best known solution of this problem."));
Operators.Add(Evaluator);
Operators.Add(new BestScopeSolutionAnalyzer());
Operators.Add(new SingleObjectiveAnalyzer());
Operators.Add(new SingleObjectiveImprover());
Operators.Add(new SingleObjectiveMoveEvaluator());
Operators.Add(new SingleObjectiveMoveGenerator());
Operators.Add(new SingleObjectiveMoveMaker());
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) { }
protected override void OnEvaluatorChanged() {
base.OnEvaluatorChanged();
ParameterizeOperators();
}
protected override void ParameterizeOperators() {
base.ParameterizeOperators();
foreach (var op in Operators.OfType())
op.EvaluateFunc = Evaluate;
foreach (var op in Operators.OfType())
op.AnalyzeAction = Analyze;
}
#region ISingleObjectiveHeuristicOptimizationProblem Members
IParameter ISingleObjectiveHeuristicOptimizationProblem.MaximizationParameter {
get { return Parameters["Maximization"]; }
}
IParameter ISingleObjectiveHeuristicOptimizationProblem.BestKnownQualityParameter {
get { return Parameters["BestKnownQuality"]; }
}
ISingleObjectiveEvaluator ISingleObjectiveHeuristicOptimizationProblem.Evaluator {
get { return Evaluator; }
}
#endregion
}
}