#region License Information
/* HeuristicLab
* Copyright (C) 2002-2019 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;
using System.Collections.Generic;
using System.Linq;
using HEAL.Attic;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Parameters;
namespace HeuristicLab.Optimization {
[StorableType("2697320D-0259-44BB-BD71-7EE1B10F664C")]
public abstract class SingleObjectiveProblem :
Problem>,
ISingleObjectiveProblem,
ISingleObjectiveProblemDefinition
where TEncoding : class, IEncoding
where TEncodedSolution : class, IEncodedSolution {
protected IValueParameter BestKnownQualityParameter {
get { return (IValueParameter)Parameters["BestKnownQuality"]; }
}
protected IFixedValueParameter MaximizationParameter {
get { return (IFixedValueParameter)Parameters["Maximization"]; }
}
public double BestKnownQuality {
get {
if (BestKnownQualityParameter.Value == null) return double.NaN;
return BestKnownQualityParameter.Value.Value;
}
set {
if (double.IsNaN(value)) {
BestKnownQualityParameter.Value = null;
return;
}
if (BestKnownQualityParameter.Value == null) BestKnownQualityParameter.Value = new DoubleValue(value);
else BestKnownQualityParameter.Value.Value = value;
}
}
[StorableConstructor]
protected SingleObjectiveProblem(StorableConstructorFlag _) : base(_) { }
protected SingleObjectiveProblem(SingleObjectiveProblem original, Cloner cloner)
: base(original, cloner) {
ParameterizeOperators();
}
protected SingleObjectiveProblem()
: base() {
Parameters.Add(new FixedValueParameter("Maximization", "Set to false if the problem should be minimized.", (BoolValue)new BoolValue(Maximization).AsReadOnly()) { Hidden = true });
Parameters.Add(new OptionalValueParameter("BestKnownQuality", "The quality of the best known solution of this problem."));
Operators.Add(Evaluator);
Operators.Add(new SingleObjectiveAnalyzer());
Operators.Add(new SingleObjectiveImprover());
Operators.Add(new SingleObjectiveMoveEvaluator());
Operators.Add(new SingleObjectiveMoveGenerator());
Operators.Add(new SingleObjectiveMoveMaker());
ParameterizeOperators();
}
protected SingleObjectiveProblem(TEncoding encoding)
: base(encoding) {
Parameters.Add(new FixedValueParameter("Maximization", "Set to false if the problem should be minimized.", (BoolValue)new BoolValue(Maximization).AsReadOnly()) { Hidden = true });
Parameters.Add(new OptionalValueParameter("BestKnownQuality", "The quality of the best known solution of this problem."));
Operators.Add(Evaluator);
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(TEncodedSolution solution, IRandom random);
public virtual void Analyze(TEncodedSolution[] solutions, double[] qualities, ResultCollection results, IRandom random) { }
public virtual IEnumerable GetNeighbors(TEncodedSolution solution, IRandom random) {
return Enumerable.Empty();
}
public virtual bool IsBetter(double quality, double bestQuality) {
return (Maximization && quality > bestQuality || !Maximization && quality < bestQuality);
}
protected Tuple GetBestSolution(TEncodedSolution[] solutions, double[] qualities) {
return GetBestSolution(solutions, qualities, Maximization);
}
public static Tuple GetBestSolution(TEncodedSolution[] solutions, double[] qualities, bool maximization) {
var zipped = solutions.Zip(qualities, (s, q) => new { Solution = s, Quality = q });
var best = (maximization ? zipped.OrderByDescending(z => z.Quality) : zipped.OrderBy(z => z.Quality)).First();
return Tuple.Create(best.Solution, best.Quality);
}
protected override void OnOperatorsChanged() {
base.OnOperatorsChanged();
if (Encoding != null) {
PruneMultiObjectiveOperators(Encoding);
var combinedEncoding = Encoding as CombinedEncoding;
if (combinedEncoding != null) {
foreach (var encoding in combinedEncoding.Encodings.ToList()) {
PruneMultiObjectiveOperators(encoding);
}
}
}
}
private void PruneMultiObjectiveOperators(IEncoding encoding) {
if (encoding.Operators.Any(x => x is IMultiObjectiveOperator && !(x is ISingleObjectiveOperator)))
encoding.Operators = encoding.Operators.Where(x => !(x is IMultiObjectiveOperator) || x is ISingleObjectiveOperator).ToList();
foreach (var multiOp in Encoding.Operators.OfType()) {
foreach (var moOp in multiOp.Operators.Where(x => x is IMultiObjectiveOperator).ToList()) {
multiOp.RemoveOperator(moOp);
}
}
}
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;
foreach (var op in Operators.OfType>())
op.GetNeighborsFunc = GetNeighbors;
}
#region ISingleObjectiveHeuristicOptimizationProblem Members
IParameter ISingleObjectiveHeuristicOptimizationProblem.MaximizationParameter {
get { return Parameters["Maximization"]; }
}
IParameter ISingleObjectiveHeuristicOptimizationProblem.BestKnownQualityParameter {
get { return Parameters["BestKnownQuality"]; }
}
ISingleObjectiveEvaluator ISingleObjectiveHeuristicOptimizationProblem.Evaluator {
get { return Evaluator; }
}
#endregion
}
}