source: branches/HeuristicLab.BinPacking/HeuristicLab.Problems.BinPacking/3.3/PackingSequenceProblem.cs @ 14128

#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 System;
using System.CodeDom;
using System.Linq;
using System.Text;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Encodings.PermutationEncoding;
using HeuristicLab.Optimization;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Problems.BinPacking;

namespace HeuristicLab.Problems.BinPacking {
  [StorableClass]
  public abstract class PackingSequenceProblem<TSolution, TEncoding> : SingleObjectiveBasicProblem<TEncoding>
    where TSolution : class, IItem
    where TEncoding : class, IEncoding {

    // persistence
    [StorableConstructor]
    protected PackingSequenceProblem(bool deserializing) : base(deserializing) { }
    [StorableHook(HookType.AfterDeserialization)]
    private void AfterDeserialization() { }


    // cloning
    protected PackingSequenceProblem(PackingSequenceProblem<TSolution, TEncoding> original, Cloner cloner)
      : base(original, cloner) {
    }

    protected PackingSequenceProblem() : base() { }

    public virtual bool IsBetter(double quality, double bestQuality) {
      return (Maximization && quality > bestQuality || !Maximization && quality < bestQuality);
    }

    public virtual void Analyze(TSolution[] solutions, double[] qualities, ResultCollection results,
      IRandom random) {
      if (!results.ContainsKey("Best Solution Quality")) {
        results.Add(new Result("Best Solution Quality", typeof(DoubleValue)));
      }
      if (!results.ContainsKey("Best Solution")) {
        results.Add(new Result("Best Solution", typeof(TSolution)));
      }

      var bestQuality = Maximization ? qualities.Max() : qualities.Min();

      if (results["Best Solution Quality"].Value == null ||
          IsBetter(bestQuality, ((DoubleValue)results["Best Solution Quality"].Value).Value)) {
        var bestIdx = Array.IndexOf(qualities, bestQuality);
        var bestClone = (IItem)solutions[bestIdx].Clone();
        results["Best Solution"].Value = bestClone;
        results["Best Solution Quality"].Value = new DoubleValue(bestQuality);
      }
    }
  }
}