#region License Information
/* HeuristicLab
* Copyright (C) 2002-2018 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.Collections.Generic;
using System.Linq;
using HeuristicLab.Analysis;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Encodings.IntegerVectorEncoding;
using HeuristicLab.Optimization;
using HeuristicLab.Optimization.Operators;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
namespace HeuristicLab.Problems.BinPacking2D {
[Item("Bin Packing Problem (2D, integer vector encoding) (BPP)", "Represents a two-dimensional bin-packing problem using only bins with identical measures and bins/items with rectangular shapes.")]
[StorableClass]
[Creatable(Category = CreatableAttribute.Categories.CombinatorialProblems, Priority = 310)]
public sealed class IntegerVectorProblem : ProblemBase {
// persistence
[StorableConstructor]
private IntegerVectorProblem(bool deserializing) : base(deserializing) { }
// cloning
private IntegerVectorProblem(IntegerVectorProblem original, Cloner cloner)
: base(original, cloner) {
RegisterEventHandlers();
}
public IntegerVectorProblem()
: base() {
Decoder = new ExtremePointIntegerVectorDecoder(); // default decoder
// the int vector contains the target bin number for each item
Encoding = new IntegerVectorEncoding(EncodedSolutionName, Items.Count, min: 0, max: LowerBound + 1); // NOTE: assumes that all items can be packed into LowerBound+1 bins
AddOperators();
Parameterize();
RegisterEventHandlers();
}
public override IDeepCloneable Clone(Cloner cloner) {
return new IntegerVectorProblem(this, cloner);
}
[StorableHook(HookType.AfterDeserialization)]
private void AfterDeserialization() {
RegisterEventHandlers();
}
protected override void OnEncodingChanged() {
base.OnEncodingChanged();
Parameterize();
}
private void AddOperators() {
// move operators are not yet supported (TODO)
Operators.RemoveAll(x => x is SingleObjectiveMoveGenerator);
Operators.RemoveAll(x => x is SingleObjectiveMoveMaker);
Operators.RemoveAll(x => x is SingleObjectiveMoveEvaluator);
Operators.Add(new HammingSimilarityCalculator());
Operators.Add(new EuclideanSimilarityCalculator());
Operators.Add(new QualitySimilarityCalculator());
Operators.Add(new PopulationSimilarityAnalyzer(Operators.OfType()));
Encoding.ConfigureOperators(Operators.OfType());
}
private void RegisterEventHandlers() {
// update encoding length when number of items is changed
ItemsParameter.ValueChanged += (sender, args) => Parameterize();
LowerBoundParameter.Value.ValueChanged += (sender, args) => Parameterize();
}
#region helpers
public static List> GenerateSequenceMatrix(IntegerVector intVec) {
List> result = new List>();
int nrOfBins = intVec.Max() + 1;
for (int i = 0; i < nrOfBins; i++)
result.Add(new List());
for (int i = 0; i < intVec.Length; i++) {
result[intVec[i]].Add(i);
}
return result;
}
private void Parameterize() {
Encoding.Length = Items.Count;
for (int i = 0; i < Encoding.Bounds.Rows; i++) {
Encoding.Bounds[i, 1] = LowerBound + 1;
}
foreach (var similarityCalculator in Operators.OfType()) {
similarityCalculator.SolutionVariableName = Encoding.SolutionCreator.IntegerVectorParameter.ActualName;
similarityCalculator.QualityVariableName = Evaluator.QualityParameter.ActualName;
}
}
#endregion
}
}