#region License Information
/* HeuristicLab
* Copyright (C) 2002-2012 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.Drawing;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Encodings.PermutationEncoding;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.PluginInfrastructure;
using HeuristicLab.Problems.Instances;
namespace HeuristicLab.Problems.QuadraticAssignment {
[Item("Quadratic Assignment Problem", "The Quadratic Assignment Problem (QAP) can be described as the problem of assigning N facilities to N fixed locations such that there is exactly one facility in each location and that the sum of the distances multiplied by the connection strength between the facilities becomes minimal.")]
[Creatable("Problems")]
[StorableClass]
public sealed class QuadraticAssignmentProblem : SingleObjectiveHeuristicOptimizationProblem, IStorableContent,
IProblemInstanceConsumer,
IProblemInstanceConsumer {
public string Filename { get; set; }
public static new Image StaticItemImage {
get { return HeuristicLab.Common.Resources.VSImageLibrary.Type; }
}
#region Parameter Properties
public IValueParameter> BestKnownSolutionsParameter {
get { return (IValueParameter>)Parameters["BestKnownSolutions"]; }
}
public IValueParameter BestKnownSolutionParameter {
get { return (IValueParameter)Parameters["BestKnownSolution"]; }
}
public IValueParameter WeightsParameter {
get { return (IValueParameter)Parameters["Weights"]; }
}
public IValueParameter DistancesParameter {
get { return (IValueParameter)Parameters["Distances"]; }
}
#endregion
#region Properties
public ItemSet BestKnownSolutions {
get { return BestKnownSolutionsParameter.Value; }
set { BestKnownSolutionsParameter.Value = value; }
}
public Permutation BestKnownSolution {
get { return BestKnownSolutionParameter.Value; }
set { BestKnownSolutionParameter.Value = value; }
}
public DoubleMatrix Weights {
get { return WeightsParameter.Value; }
set { WeightsParameter.Value = value; }
}
public DoubleMatrix Distances {
get { return DistancesParameter.Value; }
set { DistancesParameter.Value = value; }
}
private BestQAPSolutionAnalyzer BestQAPSolutionAnalyzer {
get { return Operators.OfType().FirstOrDefault(); }
}
private QAPAlleleFrequencyAnalyzer QAPAlleleFrequencyAnalyzer {
get { return Operators.OfType().FirstOrDefault(); }
}
private QAPPopulationDiversityAnalyzer QAPPopulationDiversityAnalyzer {
get { return Operators.OfType().FirstOrDefault(); }
}
#endregion
[StorableConstructor]
private QuadraticAssignmentProblem(bool deserializing) : base(deserializing) { }
private QuadraticAssignmentProblem(QuadraticAssignmentProblem original, Cloner cloner)
: base(original, cloner) {
RegisterEventHandlers();
}
public QuadraticAssignmentProblem()
: base(new QAPEvaluator(), new RandomPermutationCreator()) {
Parameters.Add(new OptionalValueParameter>("BestKnownSolutions", "The list of best known solutions which is updated whenever a new better solution is found or may be the optimal solution if it is known beforehand.", null));
Parameters.Add(new OptionalValueParameter("BestKnownSolution", "The best known solution which is updated whenever a new better solution is found or may be the optimal solution if it is known beforehand.", null));
Parameters.Add(new ValueParameter("Weights", "The strength of the connection between the facilities.", new DoubleMatrix(5, 5)));
Parameters.Add(new ValueParameter("Distances", "The distance matrix which can either be specified directly without the coordinates, or can be calculated automatically from the coordinates.", new DoubleMatrix(5, 5)));
Maximization.Value = false;
MaximizationParameter.Hidden = true;
Weights = new DoubleMatrix(new double[,] {
{ 0, 1, 0, 0, 1 },
{ 1, 0, 1, 0, 0 },
{ 0, 1, 0, 1, 0 },
{ 0, 0, 1, 0, 1 },
{ 1, 0, 0, 1, 0 }
});
Distances = new DoubleMatrix(new double[,] {
{ 0, 360, 582, 582, 360 },
{ 360, 0, 360, 582, 582 },
{ 582, 360, 0, 360, 582 },
{ 582, 582, 360, 0, 360 },
{ 360, 582, 582, 360, 0 }
});
SolutionCreator.PermutationParameter.ActualName = "Assignment";
ParameterizeSolutionCreator();
ParameterizeEvaluator();
InitializeOperators();
RegisterEventHandlers();
}
public override IDeepCloneable Clone(Cloner cloner) {
return new QuadraticAssignmentProblem(this, cloner);
}
[StorableHook(HookType.AfterDeserialization)]
private void AfterDeserialization() {
// BackwardsCompatibility3.3
#region Backwards compatible code, remove with 3.4
if (!Parameters.ContainsKey("BestKnownSolutions")) {
Parameters.Add(new OptionalValueParameter>("BestKnownSolutions", "The list of best known solutions which is updated whenever a new better solution is found or may be the optimal solution if it is known beforehand.", null));
} else if (Parameters["BestKnownSolutions"].GetType().Equals(typeof(OptionalValueParameter>))) {
ItemList list = ((OptionalValueParameter>)Parameters["BestKnownSolutions"]).Value;
Parameters.Remove("BestKnownSolutions");
Parameters.Add(new OptionalValueParameter>("BestKnownSolutions", "The list of best known solutions which is updated whenever a new better solution is found or may be the optimal solution if it is known beforehand.", (list != null ? new ItemSet(list) : null)));
}
if (Parameters.ContainsKey("DistanceMatrix")) {
DoubleMatrix d = ((ValueParameter)Parameters["DistanceMatrix"]).Value;
Parameters.Remove("DistanceMatrix");
Parameters.Add(new ValueParameter("Distances", "The distance matrix which can either be specified directly without the coordinates, or can be calculated automatically from the coordinates.", d));
}
RegisterEventHandlers();
#endregion
}
#region Events
protected override void OnSolutionCreatorChanged() {
SolutionCreator.PermutationParameter.ActualNameChanged += new EventHandler(SolutionCreator_PermutationParameter_ActualNameChanged);
ParameterizeSolutionCreator();
ParameterizeEvaluator();
ParameterizeAnalyzers();
ParameterizeOperators();
base.OnSolutionCreatorChanged();
}
protected override void OnEvaluatorChanged() {
Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
ParameterizeEvaluator();
ParameterizeAnalyzers();
ParameterizeOperators();
base.OnEvaluatorChanged();
}
private void SolutionCreator_PermutationParameter_ActualNameChanged(object sender, EventArgs e) {
ParameterizeEvaluator();
ParameterizeAnalyzers();
ParameterizeOperators();
}
private void Evaluator_QualityParameter_ActualNameChanged(object sender, EventArgs e) {
ParameterizeAnalyzers();
ParameterizeOperators();
}
private void WeightsParameter_ValueChanged(object sender, EventArgs e) {
Weights.RowsChanged += new EventHandler(Weights_RowsChanged);
Weights.ColumnsChanged += new EventHandler(Weights_ColumnsChanged);
ParameterizeSolutionCreator();
ParameterizeEvaluator();
ParameterizeOperators();
AdjustDistanceMatrix();
}
private void Weights_RowsChanged(object sender, EventArgs e) {
if (Weights.Rows != Weights.Columns)
((IStringConvertibleMatrix)Weights).Columns = Weights.Rows;
else {
ParameterizeSolutionCreator();
ParameterizeEvaluator();
ParameterizeOperators();
AdjustDistanceMatrix();
}
}
private void Weights_ColumnsChanged(object sender, EventArgs e) {
if (Weights.Rows != Weights.Columns)
((IStringConvertibleMatrix)Weights).Rows = Weights.Columns;
else {
ParameterizeSolutionCreator();
ParameterizeEvaluator();
ParameterizeOperators();
AdjustDistanceMatrix();
}
}
private void DistancesParameter_ValueChanged(object sender, EventArgs e) {
Distances.RowsChanged += new EventHandler(Distances_RowsChanged);
Distances.ColumnsChanged += new EventHandler(Distances_ColumnsChanged);
ParameterizeSolutionCreator();
ParameterizeEvaluator();
ParameterizeOperators();
AdjustWeightsMatrix();
}
private void Distances_RowsChanged(object sender, EventArgs e) {
if (Distances.Rows != Distances.Columns)
((IStringConvertibleMatrix)Distances).Columns = Distances.Rows;
else {
ParameterizeSolutionCreator();
ParameterizeEvaluator();
ParameterizeOperators();
AdjustWeightsMatrix();
}
}
private void Distances_ColumnsChanged(object sender, EventArgs e) {
if (Distances.Rows != Distances.Columns)
((IStringConvertibleMatrix)Distances).Rows = Distances.Columns;
else {
ParameterizeSolutionCreator();
ParameterizeEvaluator();
ParameterizeOperators();
AdjustWeightsMatrix();
}
}
#endregion
#region Helpers
private void RegisterEventHandlers() {
SolutionCreator.PermutationParameter.ActualNameChanged += new EventHandler(SolutionCreator_PermutationParameter_ActualNameChanged);
Evaluator.QualityParameter.ActualNameChanged += new EventHandler(Evaluator_QualityParameter_ActualNameChanged);
WeightsParameter.ValueChanged += new EventHandler(WeightsParameter_ValueChanged);
Weights.RowsChanged += new EventHandler(Weights_RowsChanged);
Weights.ColumnsChanged += new EventHandler(Weights_ColumnsChanged);
DistancesParameter.ValueChanged += new EventHandler(DistancesParameter_ValueChanged);
Distances.RowsChanged += new EventHandler(Distances_RowsChanged);
Distances.ColumnsChanged += new EventHandler(Distances_ColumnsChanged);
}
private void InitializeOperators() {
var defaultOperators = new HashSet(new IPermutationOperator[] {
new PartiallyMatchedCrossover(),
new Swap2Manipulator(),
new ExhaustiveSwap2MoveGenerator()
});
Operators.AddRange(defaultOperators);
Operators.AddRange(ApplicationManager.Manager.GetInstances().Except(defaultOperators, new TypeEqualityComparer()));
Operators.RemoveAll(x => x is ISingleObjectiveMoveEvaluator);
Operators.AddRange(ApplicationManager.Manager.GetInstances());
Operators.Add(new BestQAPSolutionAnalyzer());
Operators.Add(new QAPAlleleFrequencyAnalyzer());
Operators.Add(new QAPPopulationDiversityAnalyzer());
Operators.Add(new QAPExhaustiveSwap2LocalImprovement());
ParameterizeAnalyzers();
ParameterizeOperators();
}
private void ParameterizeSolutionCreator() {
if (SolutionCreator != null) {
SolutionCreator.PermutationTypeParameter.Value = new PermutationType(PermutationTypes.Absolute);
SolutionCreator.LengthParameter.Value = new IntValue(Weights.Rows);
}
}
private void ParameterizeEvaluator() {
if (Evaluator != null) {
Evaluator.PermutationParameter.ActualName = SolutionCreator.PermutationParameter.ActualName;
Evaluator.DistancesParameter.ActualName = DistancesParameter.Name;
Evaluator.WeightsParameter.ActualName = WeightsParameter.Name;
}
}
private void ParameterizeAnalyzers() {
if (BestQAPSolutionAnalyzer != null) {
BestQAPSolutionAnalyzer.QualityParameter.ActualName = Evaluator.QualityParameter.ActualName;
BestQAPSolutionAnalyzer.DistancesParameter.ActualName = DistancesParameter.Name;
BestQAPSolutionAnalyzer.WeightsParameter.ActualName = WeightsParameter.Name;
BestQAPSolutionAnalyzer.PermutationParameter.ActualName = SolutionCreator.PermutationParameter.ActualName;
BestQAPSolutionAnalyzer.ResultsParameter.ActualName = "Results";
BestQAPSolutionAnalyzer.BestKnownQualityParameter.ActualName = BestKnownQualityParameter.Name;
BestQAPSolutionAnalyzer.BestKnownSolutionsParameter.ActualName = BestKnownSolutionsParameter.Name;
BestQAPSolutionAnalyzer.MaximizationParameter.ActualName = MaximizationParameter.Name;
}
if (QAPAlleleFrequencyAnalyzer != null) {
QAPAlleleFrequencyAnalyzer.QualityParameter.ActualName = Evaluator.QualityParameter.ActualName;
QAPAlleleFrequencyAnalyzer.BestKnownSolutionParameter.ActualName = BestKnownSolutionParameter.Name;
QAPAlleleFrequencyAnalyzer.DistancesParameter.ActualName = DistancesParameter.Name;
QAPAlleleFrequencyAnalyzer.MaximizationParameter.ActualName = MaximizationParameter.Name;
QAPAlleleFrequencyAnalyzer.ResultsParameter.ActualName = "Results";
QAPAlleleFrequencyAnalyzer.SolutionParameter.ActualName = SolutionCreator.PermutationParameter.ActualName;
QAPAlleleFrequencyAnalyzer.WeightsParameter.ActualName = WeightsParameter.Name;
}
if (QAPPopulationDiversityAnalyzer != null) {
QAPPopulationDiversityAnalyzer.MaximizationParameter.ActualName = MaximizationParameter.Name;
QAPPopulationDiversityAnalyzer.QualityParameter.ActualName = Evaluator.QualityParameter.ActualName;
QAPPopulationDiversityAnalyzer.ResultsParameter.ActualName = "Results";
QAPPopulationDiversityAnalyzer.SolutionParameter.ActualName = SolutionCreator.PermutationParameter.ActualName;
}
}
private void ParameterizeOperators() {
foreach (IPermutationCrossover op in Operators.OfType()) {
op.ParentsParameter.ActualName = SolutionCreator.PermutationParameter.ActualName;
op.ChildParameter.ActualName = SolutionCreator.PermutationParameter.ActualName;
}
foreach (IPermutationManipulator op in Operators.OfType()) {
op.PermutationParameter.ActualName = SolutionCreator.PermutationParameter.ActualName;
}
foreach (IPermutationMoveOperator op in Operators.OfType()) {
op.PermutationParameter.ActualName = SolutionCreator.PermutationParameter.ActualName;
}
if (Operators.OfType().Any()) {
if (Operators.OfType().OfType().Any()) {
string inversionMove = Operators.OfType().OfType().First().InversionMoveParameter.ActualName;
foreach (IPermutationInversionMoveOperator op in Operators.OfType())
op.InversionMoveParameter.ActualName = inversionMove;
}
if (Operators.OfType().OfType().Any()) {
string translocationMove = Operators.OfType().OfType().First().TranslocationMoveParameter.ActualName;
foreach (IPermutationTranslocationMoveOperator op in Operators.OfType())
op.TranslocationMoveParameter.ActualName = translocationMove;
}
if (Operators.OfType().OfType().Any()) {
string swapMove = Operators.OfType().OfType().First().Swap2MoveParameter.ActualName;
foreach (IPermutationSwap2MoveOperator op in Operators.OfType()) {
op.Swap2MoveParameter.ActualName = swapMove;
}
}
}
foreach (var op in Operators.OfType())
op.PermutationParameter.ActualName = SolutionCreator.PermutationParameter.ActualName;
QAPExhaustiveSwap2LocalImprovement localOpt = Operators.OfType().SingleOrDefault();
if (localOpt != null) {
localOpt.AssignmentParameter.ActualName = SolutionCreator.PermutationParameter.ActualName;
localOpt.DistancesParameter.ActualName = DistancesParameter.Name;
localOpt.MaximizationParameter.ActualName = MaximizationParameter.Name;
localOpt.QualityParameter.ActualName = Evaluator.QualityParameter.ActualName;
localOpt.WeightsParameter.ActualName = WeightsParameter.Name;
}
}
private void AdjustDistanceMatrix() {
if (Distances.Rows != Weights.Rows || Distances.Columns != Weights.Columns) {
((IStringConvertibleMatrix)Distances).Rows = Weights.Rows;
}
}
private void AdjustWeightsMatrix() {
if (Weights.Rows != Distances.Rows || Weights.Columns != Distances.Columns) {
((IStringConvertibleMatrix)Weights).Rows = Distances.Rows;
}
}
#endregion
public void Load(QAPData data) {
var weights = new DoubleMatrix(data.Weights);
var distances = new DoubleMatrix(data.Distances);
Name = data.Name;
Description = data.Description;
Load(weights, distances);
EvaluateAndLoadAssignment(data.BestKnownAssignment);
OnReset();
}
public void Load(TSPData data) {
if (data.Dimension > 1000)
throw new System.IO.InvalidDataException("Instances with more than 1000 customers are not supported by the QAP.");
var weights = new DoubleMatrix(data.Dimension, data.Dimension);
for (int i = 0; i < data.Dimension; i++)
weights[i, (i + 1) % data.Dimension] = 1;
var distances = new DoubleMatrix(data.GetDistanceMatrix());
Name = data.Name;
Description = data.Description;
Load(weights, distances);
EvaluateAndLoadAssignment(data.BestKnownTour);
OnReset();
}
public void Load(DoubleMatrix weights, DoubleMatrix distances) {
if (weights == null || weights.Rows == 0)
throw new System.IO.InvalidDataException("The given instance does not contain weights!");
if (weights.Rows != weights.Columns)
throw new System.IO.InvalidDataException("The weights matrix is not a square matrix!");
if (distances == null || distances.Rows == 0)
throw new System.IO.InvalidDataException("The given instance does not contain distances!");
if (distances.Rows != distances.Columns)
throw new System.IO.InvalidDataException("The distances matrix is not a square matrix!");
if (weights.Rows != distances.Columns)
throw new System.IO.InvalidDataException("The weights matrix and the distance matrix are not of equal size!");
Weights = weights;
Distances = distances;
BestKnownQuality = null;
BestKnownSolution = null;
BestKnownSolutions = null;
}
public void EvaluateAndLoadAssignment(int[] assignment) {
if (assignment == null || assignment.Length == 0) return;
var vector = new Permutation(PermutationTypes.Absolute, assignment);
var result = QAPEvaluator.Apply(vector, Weights, Distances);
BestKnownQuality = new DoubleValue(result);
BestKnownSolution = vector;
BestKnownSolutions = new ItemSet();
BestKnownSolutions.Add((Permutation)vector.Clone());
}
}
}