#region License Information
/* HeuristicLab
* Copyright (C) 2002-2016 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.Globalization;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Operators;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
namespace HeuristicLab.Optimization {
[Item("Single-objective MoveGenerator", "Calls the GetNeighbors method of the problem definition to obtain the moves.")]
[StorableClass]
public class SingleObjectiveMoveGenerator : SingleSuccessorOperator, INeighborBasedOperator, IMultiMoveGenerator, IStochasticOperator, ISingleObjectiveMoveOperator {
public ILookupParameter RandomParameter {
get { return (ILookupParameter)Parameters["Random"]; }
}
public IValueLookupParameter SampleSizeParameter {
get { return (IValueLookupParameter)Parameters["SampleSize"]; }
}
public ILookupParameter EncodingParameter {
get { return (ILookupParameter)Parameters["Encoding"]; }
}
public Func> GetNeighborsFunc { get; set; }
[StorableConstructor]
protected SingleObjectiveMoveGenerator(bool deserializing) : base(deserializing) { }
protected SingleObjectiveMoveGenerator(SingleObjectiveMoveGenerator original, Cloner cloner)
: base(original, cloner) { }
public SingleObjectiveMoveGenerator() {
Parameters.Add(new LookupParameter("Random", "The random number generator to use."));
Parameters.Add(new ValueLookupParameter("SampleSize", "The number of moves to sample."));
Parameters.Add(new LookupParameter("Encoding", "An item that holds the problem's encoding."));
}
public override IDeepCloneable Clone(Cloner cloner) {
return new SingleObjectiveMoveGenerator(this, cloner);
}
public override IOperation Apply() {
var random = RandomParameter.ActualValue;
var sampleSize = SampleSizeParameter.ActualValue.Value;
var encoding = EncodingParameter.ActualValue;
var individual = encoding.GetIndividual(ExecutionContext.Scope);
var nbhood = GetNeighborsFunc(individual, random).Take(sampleSize).ToList();
var moveScopes = new Scope[nbhood.Count];
for (int i = 0; i < moveScopes.Length; i++) {
moveScopes[i] = new Scope(i.ToString(CultureInfo.InvariantCulture.NumberFormat));
nbhood[i].CopyToScope(moveScopes[i]);
}
ExecutionContext.Scope.SubScopes.AddRange(moveScopes);
return base.Apply();
}
}
}