#region License Information
/* HeuristicLab
* Copyright (C) 2002-2011 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.BinaryVectorEncoding;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.PluginInfrastructure;
namespace HeuristicLab.Problems.Knapsack {
[Item("Knapsack Problem", "Represents a Knapsack problem.")]
[Creatable("Problems")]
[StorableClass]
public sealed class KnapsackProblem : ParameterizedNamedItem, ISingleObjectiveHeuristicOptimizationProblem, IStorableContent {
public string Filename { get; set; }
public override Image ItemImage {
get { return HeuristicLab.Common.Resources.VSImageLibrary.Type; }
}
#region Parameter Properties
public ValueParameter MaximizationParameter {
get { return (ValueParameter)Parameters["Maximization"]; }
}
IParameter ISingleObjectiveHeuristicOptimizationProblem.MaximizationParameter {
get { return MaximizationParameter; }
}
public ValueParameter KnapsackCapacityParameter {
get { return (ValueParameter)Parameters["KnapsackCapacity"]; }
}
public ValueParameter WeightsParameter {
get { return (ValueParameter)Parameters["Weights"]; }
}
public ValueParameter ValuesParameter {
get { return (ValueParameter)Parameters["Values"]; }
}
public ValueParameter PenaltyParameter {
get { return (ValueParameter)Parameters["Penalty"]; }
}
public ValueParameter SolutionCreatorParameter {
get { return (ValueParameter)Parameters["SolutionCreator"]; }
}
IParameter IHeuristicOptimizationProblem.SolutionCreatorParameter {
get { return SolutionCreatorParameter; }
}
public ValueParameter EvaluatorParameter {
get { return (ValueParameter)Parameters["Evaluator"]; }
}
IParameter IHeuristicOptimizationProblem.EvaluatorParameter {
get { return EvaluatorParameter; }
}
public OptionalValueParameter BestKnownQualityParameter {
get { return (OptionalValueParameter)Parameters["BestKnownQuality"]; }
}
IParameter ISingleObjectiveHeuristicOptimizationProblem.BestKnownQualityParameter {
get { return BestKnownQualityParameter; }
}
public OptionalValueParameter BestKnownSolutionParameter {
get { return (OptionalValueParameter)Parameters["BestKnownSolution"]; }
}
#endregion
#region Properties
public IntValue KnapsackCapacity {
get { return KnapsackCapacityParameter.Value; }
set { KnapsackCapacityParameter.Value = value; }
}
public IntArray Weights {
get { return WeightsParameter.Value; }
set { WeightsParameter.Value = value; }
}
public IntArray Values {
get { return ValuesParameter.Value; }
set { ValuesParameter.Value = value; }
}
public DoubleValue Penalty {
get { return PenaltyParameter.Value; }
set { PenaltyParameter.Value = value; }
}
public IBinaryVectorCreator SolutionCreator {
get { return SolutionCreatorParameter.Value; }
set { SolutionCreatorParameter.Value = value; }
}
ISolutionCreator IHeuristicOptimizationProblem.SolutionCreator {
get { return SolutionCreatorParameter.Value; }
}
public IKnapsackEvaluator Evaluator {
get { return EvaluatorParameter.Value; }
set { EvaluatorParameter.Value = value; }
}
ISingleObjectiveEvaluator ISingleObjectiveHeuristicOptimizationProblem.Evaluator {
get { return EvaluatorParameter.Value; }
}
IEvaluator IHeuristicOptimizationProblem.Evaluator {
get { return EvaluatorParameter.Value; }
}
public DoubleValue BestKnownQuality {
get { return BestKnownQualityParameter.Value; }
set { BestKnownQualityParameter.Value = value; }
}
public BinaryVector BestKnownSolution {
get { return BestKnownSolutionParameter.Value; }
set { BestKnownSolutionParameter.Value = value; }
}
public IEnumerable Operators {
get { return operators.Cast(); }
}
private BestKnapsackSolutionAnalyzer BestKnapsackSolutionAnalyzer {
get { return operators.OfType().FirstOrDefault(); }
}
#endregion
[Storable]
private List operators;
[StorableConstructor]
private KnapsackProblem(bool deserializing) : base(deserializing) { }
private KnapsackProblem(KnapsackProblem original, Cloner cloner)
: base(original, cloner) {
this.operators = original.operators.Select(x => (IOperator)cloner.Clone(x)).ToList();
AttachEventHandlers();
}
public override IDeepCloneable Clone(Cloner cloner) {
return new KnapsackProblem(this, cloner);
}
public KnapsackProblem()
: base() {
RandomBinaryVectorCreator creator = new RandomBinaryVectorCreator();
KnapsackEvaluator evaluator = new KnapsackEvaluator();
Parameters.Add(new ValueParameter("Maximization", "Set to true as the Knapsack Problem is a maximization problem.", new BoolValue(true)));
Parameters.Add(new ValueParameter("KnapsackCapacity", "Capacity of the Knapsack.", new IntValue(0)));
Parameters.Add(new ValueParameter("Weights", "The weights of the items.", new IntArray(5)));
Parameters.Add(new ValueParameter("Values", "The values of the items.", new IntArray(5)));
Parameters.Add(new ValueParameter("Penalty", "The penalty value for each unit of overweight.", new DoubleValue(1)));
Parameters.Add(new ValueParameter("SolutionCreator", "The operator which should be used to create new Knapsack solutions.", creator));
Parameters.Add(new ValueParameter("Evaluator", "The operator which should be used to evaluate Knapsack solutions.", evaluator));
Parameters.Add(new OptionalValueParameter("BestKnownQuality", "The quality of the best known solution of this Knapsack instance."));
Parameters.Add(new OptionalValueParameter("BestKnownSolution", "The best known solution of this Knapsack instance."));
creator.BinaryVectorParameter.ActualName = "KnapsackSolution";
InitializeRandomKnapsackInstance();
ParameterizeSolutionCreator();
ParameterizeEvaluator();
InitializeOperators();
AttachEventHandlers();
}
#region Events
public event EventHandler SolutionCreatorChanged;
private void OnSolutionCreatorChanged() {
EventHandler handler = SolutionCreatorChanged;
if (handler != null) handler(this, EventArgs.Empty);
}
public event EventHandler EvaluatorChanged;
private void OnEvaluatorChanged() {
EventHandler handler = EvaluatorChanged;
if (handler != null) handler(this, EventArgs.Empty);
}
public event EventHandler OperatorsChanged;
private void OnOperatorsChanged() {
EventHandler handler = OperatorsChanged;
if (handler != null) handler(this, EventArgs.Empty);
}
public event EventHandler Reset;
private void OnReset() {
EventHandler handler = Reset;
if (handler != null) handler(this, EventArgs.Empty);
}
private void SolutionCreatorParameter_ValueChanged(object sender, EventArgs e) {
SolutionCreator.BinaryVectorParameter.ActualNameChanged += new EventHandler(SolutionCreator_BinaryVectorParameter_ActualNameChanged);
ParameterizeSolutionCreator();
ParameterizeEvaluator();
ParameterizeAnalyzer();
ParameterizeOperators();
OnSolutionCreatorChanged();
}
private void SolutionCreator_BinaryVectorParameter_ActualNameChanged(object sender, EventArgs e) {
ParameterizeEvaluator();
ParameterizeAnalyzer();
ParameterizeOperators();
}
private void EvaluatorParameter_ValueChanged(object sender, EventArgs e) {
ParameterizeEvaluator();
ParameterizeAnalyzer();
OnEvaluatorChanged();
}
void KnapsackCapacityParameter_ValueChanged(object sender, EventArgs e) {
ParameterizeEvaluator();
ParameterizeAnalyzer();
}
void WeightsParameter_ValueChanged(object sender, EventArgs e) {
ParameterizeEvaluator();
ParameterizeAnalyzer();
ParameterizeSolutionCreator();
WeightsParameter.Value.Reset += new EventHandler(WeightsValue_Reset);
}
void WeightsValue_Reset(object sender, EventArgs e) {
ParameterizeSolutionCreator();
if (WeightsParameter.Value != null && ValuesParameter.Value != null)
((IStringConvertibleArray)ValuesParameter.Value).Length = WeightsParameter.Value.Length;
}
void ValuesParameter_ValueChanged(object sender, EventArgs e) {
ParameterizeEvaluator();
ParameterizeAnalyzer();
ParameterizeSolutionCreator();
ValuesParameter.Value.Reset += new EventHandler(ValuesValue_Reset);
}
void ValuesValue_Reset(object sender, EventArgs e) {
ParameterizeSolutionCreator();
if (WeightsParameter.Value != null && ValuesParameter.Value != null)
((IStringConvertibleArray)WeightsParameter.Value).Length = ValuesParameter.Value.Length;
}
void PenaltyParameter_ValueChanged(object sender, EventArgs e) {
ParameterizeEvaluator();
}
void OneBitflipMoveParameter_ActualNameChanged(object sender, EventArgs e) {
string name = ((ILookupParameter)sender).ActualName;
foreach (IOneBitflipMoveOperator op in Operators.OfType()) {
op.OneBitflipMoveParameter.ActualName = name;
}
}
#endregion
#region Helpers
[StorableHook(HookType.AfterDeserialization)]
private void AfterDeserialization() {
// BackwardsCompatibility3.3
#region Backwards compatible code (remove with 3.4)
if (operators == null) InitializeOperators();
#endregion
AttachEventHandlers();
}
private void AttachEventHandlers() {
SolutionCreatorParameter.ValueChanged += new EventHandler(SolutionCreatorParameter_ValueChanged);
SolutionCreator.BinaryVectorParameter.ActualNameChanged += new EventHandler(SolutionCreator_BinaryVectorParameter_ActualNameChanged);
EvaluatorParameter.ValueChanged += new EventHandler(EvaluatorParameter_ValueChanged);
KnapsackCapacityParameter.ValueChanged += new EventHandler(KnapsackCapacityParameter_ValueChanged);
WeightsParameter.ValueChanged += new EventHandler(WeightsParameter_ValueChanged);
WeightsParameter.Value.Reset += new EventHandler(WeightsValue_Reset);
ValuesParameter.ValueChanged += new EventHandler(ValuesParameter_ValueChanged);
ValuesParameter.Value.Reset += new EventHandler(ValuesValue_Reset);
PenaltyParameter.ValueChanged += new EventHandler(PenaltyParameter_ValueChanged);
}
private void ParameterizeSolutionCreator() {
if (SolutionCreator.LengthParameter.Value == null ||
SolutionCreator.LengthParameter.Value.Value != WeightsParameter.Value.Length)
SolutionCreator.LengthParameter.Value = new IntValue(WeightsParameter.Value.Length);
}
private void ParameterizeEvaluator() {
if (Evaluator is KnapsackEvaluator) {
KnapsackEvaluator knapsackEvaluator =
(KnapsackEvaluator)Evaluator;
knapsackEvaluator.BinaryVectorParameter.ActualName = SolutionCreator.BinaryVectorParameter.ActualName;
knapsackEvaluator.KnapsackCapacityParameter.ActualName = KnapsackCapacityParameter.Name;
knapsackEvaluator.WeightsParameter.ActualName = WeightsParameter.Name;
knapsackEvaluator.ValuesParameter.ActualName = ValuesParameter.Name;
knapsackEvaluator.PenaltyParameter.ActualName = PenaltyParameter.Name;
}
}
private void ParameterizeAnalyzer() {
BestKnapsackSolutionAnalyzer.MaximizationParameter.ActualName = MaximizationParameter.Name;
BestKnapsackSolutionAnalyzer.BestKnownQualityParameter.ActualName = BestKnownQualityParameter.Name;
BestKnapsackSolutionAnalyzer.BestKnownSolutionParameter.ActualName = BestKnownSolutionParameter.Name;
BestKnapsackSolutionAnalyzer.BinaryVectorParameter.ActualName = SolutionCreator.BinaryVectorParameter.ActualName;
BestKnapsackSolutionAnalyzer.KnapsackCapacityParameter.ActualName = KnapsackCapacityParameter.Name;
BestKnapsackSolutionAnalyzer.WeightsParameter.ActualName = WeightsParameter.Name;
BestKnapsackSolutionAnalyzer.ValuesParameter.ActualName = ValuesParameter.Name;
BestKnapsackSolutionAnalyzer.ResultsParameter.ActualName = "Results";
}
private void InitializeOperators() {
operators = new List();
operators.Add(new BestKnapsackSolutionAnalyzer());
ParameterizeAnalyzer();
foreach (IBinaryVectorOperator op in ApplicationManager.Manager.GetInstances()) {
if (!(op is ISingleObjectiveMoveEvaluator) || (op is IKnapsackMoveEvaluator)) {
operators.Add(op);
}
}
ParameterizeOperators();
InitializeMoveGenerators();
}
private void InitializeMoveGenerators() {
foreach (IOneBitflipMoveOperator op in Operators.OfType()) {
if (op is IMoveGenerator) {
op.OneBitflipMoveParameter.ActualNameChanged += new EventHandler(OneBitflipMoveParameter_ActualNameChanged);
}
}
}
private void ParameterizeOperators() {
foreach (IBinaryVectorCrossover op in Operators.OfType()) {
op.ParentsParameter.ActualName = SolutionCreator.BinaryVectorParameter.ActualName;
op.ChildParameter.ActualName = SolutionCreator.BinaryVectorParameter.ActualName;
}
foreach (IBinaryVectorManipulator op in Operators.OfType()) {
op.BinaryVectorParameter.ActualName = SolutionCreator.BinaryVectorParameter.ActualName;
}
foreach (IBinaryVectorMoveOperator op in Operators.OfType()) {
op.BinaryVectorParameter.ActualName = SolutionCreator.BinaryVectorParameter.ActualName;
}
foreach (IKnapsackMoveEvaluator op in Operators.OfType()) {
op.KnapsackCapacityParameter.ActualName = KnapsackCapacityParameter.Name;
op.PenaltyParameter.ActualName = PenaltyParameter.Name;
op.WeightsParameter.ActualName = WeightsParameter.Name;
op.ValuesParameter.ActualName = ValuesParameter.Name;
}
}
#endregion
private void InitializeRandomKnapsackInstance() {
System.Random rand = new System.Random();
int itemCount = rand.Next(10, 100);
Weights = new IntArray(itemCount);
Values = new IntArray(itemCount);
double totalWeight = 0;
for (int i = 0; i < itemCount; i++) {
int value = rand.Next(1, 10);
int weight = rand.Next(1, 10);
Values[i] = value;
Weights[i] = weight;
totalWeight += weight;
}
int capacity = (int)Math.Round(0.7 * totalWeight);
KnapsackCapacity = new IntValue(capacity);
}
}
}