source: branches/PerformanceComparison/HeuristicLab.Analysis.FitnessLandscape/3.3/Algorithms/UpDownWalk.cs @ 13583

#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 <http://www.gnu.org/licenses/>.
 */
#endregion

using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;

namespace HeuristicLab.Analysis.FitnessLandscape {
  [Item("Up/Down Walk", "An up/down walk attempts to take the best of the sample until no better can be found and then switch to take the worse until no worse can be found.")]
  [StorableClass]
  [Creatable(CreatableAttribute.Categories.TestingAndAnalysis + CreatableAttribute.Categories.SplitToken + "1" + CreatableAttribute.Categories.OrderToken + "FLA", Priority = 302)]
  public sealed class UpDownWalk : LocalAnalysis<UpDownSelector> {

    public IFixedValueParameter<IntValue> SampleSizeParameter {
      get { return (IFixedValueParameter<IntValue>)Parameters["SampleSize"]; }
    }

    [StorableConstructor]
    private UpDownWalk(bool deserializing) : base(deserializing) { }
    private UpDownWalk(UpDownWalk original, Cloner cloner) : base(original, cloner) { }
    public UpDownWalk()
      : base(new UpDownSelector()) {
      Parameters.Add(new FixedValueParameter<IntValue>("SampleSize", "Number of moves that MultiMoveGenerators should create. This is ignored for Exhaustive- and SingleMoveGenerators.", new IntValue(10)));

      VariableCreator.CollectedValues.Add(new ValueParameter<BoolValue>("MoveTowardsOptimum", new BoolValue(true)));
      VariableCreator.CollectedValues.Add(new ValueParameter<DoubleValue>("BaseQuality", new DoubleValue(double.NaN)));

      SelectorParameter.Value.BaseQualityParameter.ActualName = "BaseQuality";
      SelectorParameter.Value.MoveTowardsOptimumParameter.ActualName = "MoveTowardsOptimum";
    }

    protected override void Parameterize() {
      base.Parameterize();
      if (Problem == null) return;
      SelectorParameter.Value.QualityParameter.ActualName = Problem.Evaluator.QualityParameter.ActualName;
    }

    public override IDeepCloneable Clone(Cloner cloner) {
      return new UpDownWalk(this, cloner);
    }
  }
}