#region License Information
/* HeuristicLab
* Copyright (C) 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 System.Threading;
using HEAL.Attic;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Operators;
using HeuristicLab.Parameters;
namespace HeuristicLab.Optimization {
[Item("Single-objective Improver", "Improves a solution by calling GetNeighbors and Evaluate of the corresponding problem definition.")]
[StorableType("7A917E09-920C-4B47-9599-67371101B35F")]
internal sealed class SingleObjectiveImprover : SingleSuccessorOperator, INeighborBasedOperator, IImprovementOperator, ISingleObjectiveEvaluationOperator, IStochasticOperator
where TEncodedSolution : class, IEncodedSolution {
public ILookupParameter RandomParameter {
get { return (ILookupParameter)Parameters["Random"]; }
}
public ILookupParameter> EncodingParameter {
get { return (ILookupParameter>)Parameters["Encoding"]; }
}
public ILookupParameter QualityParameter {
get { return (ILookupParameter)Parameters["Quality"]; }
}
public ILookupParameter MaximizationParameter {
get { return (ILookupParameter)Parameters["Maximization"]; }
}
public IValueLookupParameter ImprovementAttemptsParameter {
get { return (IValueLookupParameter)Parameters["ImprovementAttempts"]; }
}
public IValueLookupParameter SampleSizeParameter {
get { return (IValueLookupParameter)Parameters["SampleSize"]; }
}
public ILookupParameter LocalEvaluatedSolutionsParameter {
get { return (ILookupParameter)Parameters["LocalEvaluatedSolutions"]; }
}
public Action, IRandom, CancellationToken> Evaluate { get; set; }
public Func, IRandom, IEnumerable>> GetNeighbors { get; set; }
[StorableConstructor]
private SingleObjectiveImprover(StorableConstructorFlag _) : base(_) { }
private SingleObjectiveImprover(SingleObjectiveImprover original, Cloner cloner) : base(original, cloner) { }
public SingleObjectiveImprover() {
Parameters.Add(new LookupParameter("Random", "The random number generator to use."));
Parameters.Add(new LookupParameter>("Encoding", "An item that holds the problem's encoding."));
Parameters.Add(new LookupParameter("Quality", "The quality of the parameter vector."));
Parameters.Add(new LookupParameter("Maximization", "Whether the problem should be minimized or maximized."));
Parameters.Add(new ValueLookupParameter("ImprovementAttempts", "The number of improvement attempts the operator should perform.", new IntValue(100)));
Parameters.Add(new ValueLookupParameter("SampleSize", "The number of samples to draw from the neighborhood function at maximum.", new IntValue(300)));
Parameters.Add(new LookupParameter("LocalEvaluatedSolutions", "The number of solution evaluations that have been performed."));
}
public override IDeepCloneable Clone(Cloner cloner) {
return new SingleObjectiveImprover(this, cloner);
}
public override IOperation Apply() {
var random = RandomParameter.ActualValue;
var encoding = EncodingParameter.ActualValue;
var maximize = MaximizationParameter.ActualValue.Value;
var maxAttempts = ImprovementAttemptsParameter.ActualValue.Value;
var sampleSize = SampleSizeParameter.ActualValue.Value;
var solutionContext = ScopeUtil.CreateSolutionContext(ExecutionContext.Scope, encoding);
double quality;
if (QualityParameter.ActualValue == null) {
if (!solutionContext.IsEvaluated) Evaluate(solutionContext, random, CancellationToken.None);
quality = solutionContext.EvaluationResult.Quality;
} else quality = QualityParameter.ActualValue.Value;
var count = 0;
for (var i = 0; i < maxAttempts; i++) {
ISingleObjectiveSolutionContext best = default;
var bestQuality = quality;
foreach (var neighbor in GetNeighbors(solutionContext, random).Take(sampleSize)) {
if (!neighbor.IsEvaluated)
Evaluate(neighbor, random, CancellationToken);
var q = neighbor.EvaluationResult.Quality;
count++;
if (maximize && bestQuality > q || !maximize && bestQuality < q) continue;
best = neighbor;
bestQuality = q;
}
if (best == null) break;
solutionContext = best;
quality = bestQuality;
}
LocalEvaluatedSolutionsParameter.ActualValue = new IntValue(count);
QualityParameter.ActualValue = new DoubleValue(quality);
ScopeUtil.CopyEncodedSolutionToScope(ExecutionContext.Scope, encoding, solutionContext.EncodedSolution);
ScopeUtil.CopyToScope(ExecutionContext.Scope, solutionContext);
return base.Apply();
}
}
}