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source: trunk/sources/HeuristicLab.Problems.Knapsack/3.3/KnapsackProblem.cs @ 6347

Last change on this file since 6347 was 6053, checked in by abeham, 14 years ago

#1377

  • Added hiding to some more algorithms and problems
File size: 17.6 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2011 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using System;
23using System.Collections.Generic;
24using System.Drawing;
25using System.Linq;
26using HeuristicLab.Common;
27using HeuristicLab.Core;
28using HeuristicLab.Data;
29using HeuristicLab.Encodings.BinaryVectorEncoding;
30using HeuristicLab.Optimization;
31using HeuristicLab.Parameters;
32using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
33using HeuristicLab.PluginInfrastructure;
34
35namespace HeuristicLab.Problems.Knapsack {
36  [Item("Knapsack Problem", "Represents a Knapsack problem.")]
37  [Creatable("Problems")]
38  [StorableClass]
39  public sealed class KnapsackProblem : ParameterizedNamedItem, ISingleObjectiveHeuristicOptimizationProblem, IStorableContent {
40    public string Filename { get; set; }
41
42    public override Image ItemImage {
43      get { return HeuristicLab.Common.Resources.VSImageLibrary.Type; }
44    }
45
46    #region Parameter Properties
47    public ValueParameter<BoolValue> MaximizationParameter {
48      get { return (ValueParameter<BoolValue>)Parameters["Maximization"]; }
49    }
50    IParameter ISingleObjectiveHeuristicOptimizationProblem.MaximizationParameter {
51      get { return MaximizationParameter; }
52    }
53    public ValueParameter<IntValue> KnapsackCapacityParameter {
54      get { return (ValueParameter<IntValue>)Parameters["KnapsackCapacity"]; }
55    }
56    public ValueParameter<IntArray> WeightsParameter {
57      get { return (ValueParameter<IntArray>)Parameters["Weights"]; }
58    }
59    public ValueParameter<IntArray> ValuesParameter {
60      get { return (ValueParameter<IntArray>)Parameters["Values"]; }
61    }
62    public ValueParameter<DoubleValue> PenaltyParameter {
63      get { return (ValueParameter<DoubleValue>)Parameters["Penalty"]; }
64    }
65    public ValueParameter<IBinaryVectorCreator> SolutionCreatorParameter {
66      get { return (ValueParameter<IBinaryVectorCreator>)Parameters["SolutionCreator"]; }
67    }
68    IParameter IHeuristicOptimizationProblem.SolutionCreatorParameter {
69      get { return SolutionCreatorParameter; }
70    }
71    public ValueParameter<IKnapsackEvaluator> EvaluatorParameter {
72      get { return (ValueParameter<IKnapsackEvaluator>)Parameters["Evaluator"]; }
73    }
74    IParameter IHeuristicOptimizationProblem.EvaluatorParameter {
75      get { return EvaluatorParameter; }
76    }
77    public OptionalValueParameter<DoubleValue> BestKnownQualityParameter {
78      get { return (OptionalValueParameter<DoubleValue>)Parameters["BestKnownQuality"]; }
79    }
80    IParameter ISingleObjectiveHeuristicOptimizationProblem.BestKnownQualityParameter {
81      get { return BestKnownQualityParameter; }
82    }
83    public OptionalValueParameter<BinaryVector> BestKnownSolutionParameter {
84      get { return (OptionalValueParameter<BinaryVector>)Parameters["BestKnownSolution"]; }
85    }
86    #endregion
87
88    #region Properties
89    public IntValue KnapsackCapacity {
90      get { return KnapsackCapacityParameter.Value; }
91      set { KnapsackCapacityParameter.Value = value; }
92    }
93    public IntArray Weights {
94      get { return WeightsParameter.Value; }
95      set { WeightsParameter.Value = value; }
96    }
97    public IntArray Values {
98      get { return ValuesParameter.Value; }
99      set { ValuesParameter.Value = value; }
100    }
101    public DoubleValue Penalty {
102      get { return PenaltyParameter.Value; }
103      set { PenaltyParameter.Value = value; }
104    }
105    public IBinaryVectorCreator SolutionCreator {
106      get { return SolutionCreatorParameter.Value; }
107      set { SolutionCreatorParameter.Value = value; }
108    }
109    ISolutionCreator IHeuristicOptimizationProblem.SolutionCreator {
110      get { return SolutionCreatorParameter.Value; }
111    }
112    public IKnapsackEvaluator Evaluator {
113      get { return EvaluatorParameter.Value; }
114      set { EvaluatorParameter.Value = value; }
115    }
116    ISingleObjectiveEvaluator ISingleObjectiveHeuristicOptimizationProblem.Evaluator {
117      get { return EvaluatorParameter.Value; }
118    }
119    IEvaluator IHeuristicOptimizationProblem.Evaluator {
120      get { return EvaluatorParameter.Value; }
121    }
122    public DoubleValue BestKnownQuality {
123      get { return BestKnownQualityParameter.Value; }
124      set { BestKnownQualityParameter.Value = value; }
125    }
126    public BinaryVector BestKnownSolution {
127      get { return BestKnownSolutionParameter.Value; }
128      set { BestKnownSolutionParameter.Value = value; }
129    }
130    public IEnumerable<IOperator> Operators {
131      get { return operators.Cast<IOperator>(); }
132    }
133    private BestKnapsackSolutionAnalyzer BestKnapsackSolutionAnalyzer {
134      get { return operators.OfType<BestKnapsackSolutionAnalyzer>().FirstOrDefault(); }
135    }
136    #endregion
137
138    [Storable]
139    private List<IOperator> operators;
140
141    [StorableConstructor]
142    private KnapsackProblem(bool deserializing) : base(deserializing) { }
143    private KnapsackProblem(KnapsackProblem original, Cloner cloner)
144      : base(original, cloner) {
145      this.operators = original.operators.Select(x => (IOperator)cloner.Clone(x)).ToList();
146      AttachEventHandlers();
147    }
148    public override IDeepCloneable Clone(Cloner cloner) {
149      return new KnapsackProblem(this, cloner);
150    }
151    public KnapsackProblem()
152      : base() {
153      RandomBinaryVectorCreator creator = new RandomBinaryVectorCreator();
154      KnapsackEvaluator evaluator = new KnapsackEvaluator();
155
156      Parameters.Add(new ValueParameter<BoolValue>("Maximization", "Set to true as the Knapsack Problem is a maximization problem.", new BoolValue(true)));
157      Parameters.Add(new ValueParameter<IntValue>("KnapsackCapacity", "Capacity of the Knapsack.", new IntValue(0)));
158      Parameters.Add(new ValueParameter<IntArray>("Weights", "The weights of the items.", new IntArray(5)));
159      Parameters.Add(new ValueParameter<IntArray>("Values", "The values of the items.", new IntArray(5)));
160      Parameters.Add(new ValueParameter<DoubleValue>("Penalty", "The penalty value for each unit of overweight.", new DoubleValue(1)));
161      Parameters.Add(new ValueParameter<IBinaryVectorCreator>("SolutionCreator", "The operator which should be used to create new Knapsack solutions.", creator));
162      Parameters.Add(new ValueParameter<IKnapsackEvaluator>("Evaluator", "The operator which should be used to evaluate Knapsack solutions.", evaluator));
163      Parameters.Add(new OptionalValueParameter<DoubleValue>("BestKnownQuality", "The quality of the best known solution of this Knapsack instance."));
164      Parameters.Add(new OptionalValueParameter<BinaryVector>("BestKnownSolution", "The best known solution of this Knapsack instance."));
165
166      creator.BinaryVectorParameter.ActualName = "KnapsackSolution";
167
168      InitializeRandomKnapsackInstance();
169
170      ParameterizeSolutionCreator();
171      ParameterizeEvaluator();
172
173      InitializeOperators();
174      AttachEventHandlers();
175    }
176
177    #region Events
178    public event EventHandler SolutionCreatorChanged;
179    private void OnSolutionCreatorChanged() {
180      EventHandler handler = SolutionCreatorChanged;
181      if (handler != null) handler(this, EventArgs.Empty);
182    }
183    public event EventHandler EvaluatorChanged;
184    private void OnEvaluatorChanged() {
185      EventHandler handler = EvaluatorChanged;
186      if (handler != null) handler(this, EventArgs.Empty);
187    }
188    public event EventHandler OperatorsChanged;
189    private void OnOperatorsChanged() {
190      EventHandler handler = OperatorsChanged;
191      if (handler != null) handler(this, EventArgs.Empty);
192    }
193    public event EventHandler Reset;
194    private void OnReset() {
195      EventHandler handler = Reset;
196      if (handler != null) handler(this, EventArgs.Empty);
197    }
198
199    private void SolutionCreatorParameter_ValueChanged(object sender, EventArgs e) {
200      SolutionCreator.BinaryVectorParameter.ActualNameChanged += new EventHandler(SolutionCreator_BinaryVectorParameter_ActualNameChanged);
201      ParameterizeSolutionCreator();
202      ParameterizeEvaluator();
203      ParameterizeAnalyzer();
204      ParameterizeOperators();
205      OnSolutionCreatorChanged();
206    }
207    private void SolutionCreator_BinaryVectorParameter_ActualNameChanged(object sender, EventArgs e) {
208      ParameterizeEvaluator();
209      ParameterizeAnalyzer();
210      ParameterizeOperators();
211    }
212    private void EvaluatorParameter_ValueChanged(object sender, EventArgs e) {
213      ParameterizeEvaluator();
214      ParameterizeAnalyzer();
215      OnEvaluatorChanged();
216    }
217    void KnapsackCapacityParameter_ValueChanged(object sender, EventArgs e) {
218      ParameterizeEvaluator();
219      ParameterizeAnalyzer();
220    }
221    void WeightsParameter_ValueChanged(object sender, EventArgs e) {
222      ParameterizeEvaluator();
223      ParameterizeAnalyzer();
224      ParameterizeSolutionCreator();
225
226      WeightsParameter.Value.Reset += new EventHandler(WeightsValue_Reset);
227    }
228    void WeightsValue_Reset(object sender, EventArgs e) {
229      ParameterizeSolutionCreator();
230
231      if (WeightsParameter.Value != null && ValuesParameter.Value != null)
232        ((IStringConvertibleArray)ValuesParameter.Value).Length = WeightsParameter.Value.Length;
233    }
234    void ValuesParameter_ValueChanged(object sender, EventArgs e) {
235      ParameterizeEvaluator();
236      ParameterizeAnalyzer();
237      ParameterizeSolutionCreator();
238
239      ValuesParameter.Value.Reset += new EventHandler(ValuesValue_Reset);
240    }
241    void ValuesValue_Reset(object sender, EventArgs e) {
242      ParameterizeSolutionCreator();
243
244      if (WeightsParameter.Value != null && ValuesParameter.Value != null)
245        ((IStringConvertibleArray)WeightsParameter.Value).Length = ValuesParameter.Value.Length;
246    }
247    void PenaltyParameter_ValueChanged(object sender, EventArgs e) {
248      ParameterizeEvaluator();
249    }
250    void OneBitflipMoveParameter_ActualNameChanged(object sender, EventArgs e) {
251      string name = ((ILookupParameter<OneBitflipMove>)sender).ActualName;
252      foreach (IOneBitflipMoveOperator op in Operators.OfType<IOneBitflipMoveOperator>()) {
253        op.OneBitflipMoveParameter.ActualName = name;
254      }
255    }
256    #endregion
257
258    #region Helpers
259    [StorableHook(HookType.AfterDeserialization)]
260    private void AfterDeserialization() {
261      // BackwardsCompatibility3.3
262      #region Backwards compatible code (remove with 3.4)
263      if (operators == null) InitializeOperators();
264      #endregion
265      AttachEventHandlers();
266    }
267
268    private void AttachEventHandlers() {
269      SolutionCreatorParameter.ValueChanged += new EventHandler(SolutionCreatorParameter_ValueChanged);
270      SolutionCreator.BinaryVectorParameter.ActualNameChanged += new EventHandler(SolutionCreator_BinaryVectorParameter_ActualNameChanged);
271      EvaluatorParameter.ValueChanged += new EventHandler(EvaluatorParameter_ValueChanged);
272      KnapsackCapacityParameter.ValueChanged += new EventHandler(KnapsackCapacityParameter_ValueChanged);
273      WeightsParameter.ValueChanged += new EventHandler(WeightsParameter_ValueChanged);
274      WeightsParameter.Value.Reset += new EventHandler(WeightsValue_Reset);
275      ValuesParameter.ValueChanged += new EventHandler(ValuesParameter_ValueChanged);
276      ValuesParameter.Value.Reset += new EventHandler(ValuesValue_Reset);
277      PenaltyParameter.ValueChanged += new EventHandler(PenaltyParameter_ValueChanged);
278    }
279    private void ParameterizeSolutionCreator() {
280      if (SolutionCreator.LengthParameter.Value == null ||
281        SolutionCreator.LengthParameter.Value.Value != WeightsParameter.Value.Length)
282        SolutionCreator.LengthParameter.Value = new IntValue(WeightsParameter.Value.Length);
283    }
284    private void ParameterizeEvaluator() {
285      if (Evaluator is KnapsackEvaluator) {
286        KnapsackEvaluator knapsackEvaluator =
287          (KnapsackEvaluator)Evaluator;
288        knapsackEvaluator.BinaryVectorParameter.ActualName = SolutionCreator.BinaryVectorParameter.ActualName;
289        knapsackEvaluator.BinaryVectorParameter.Hidden = true;
290        knapsackEvaluator.KnapsackCapacityParameter.ActualName = KnapsackCapacityParameter.Name;
291        knapsackEvaluator.KnapsackCapacityParameter.Hidden = true;
292        knapsackEvaluator.WeightsParameter.ActualName = WeightsParameter.Name;
293        knapsackEvaluator.WeightsParameter.Hidden = true;
294        knapsackEvaluator.ValuesParameter.ActualName = ValuesParameter.Name;
295        knapsackEvaluator.ValuesParameter.Hidden = true;
296        knapsackEvaluator.PenaltyParameter.ActualName = PenaltyParameter.Name;
297        knapsackEvaluator.PenaltyParameter.Hidden = true;
298      }
299    }
300    private void ParameterizeAnalyzer() {
301      BestKnapsackSolutionAnalyzer.MaximizationParameter.ActualName = MaximizationParameter.Name;
302      BestKnapsackSolutionAnalyzer.MaximizationParameter.Hidden = true;
303      BestKnapsackSolutionAnalyzer.BestKnownQualityParameter.ActualName = BestKnownQualityParameter.Name;
304      BestKnapsackSolutionAnalyzer.BestKnownQualityParameter.Hidden = true;
305      BestKnapsackSolutionAnalyzer.BestKnownSolutionParameter.ActualName = BestKnownSolutionParameter.Name;
306      BestKnapsackSolutionAnalyzer.BestKnownSolutionParameter.Hidden = true;
307      BestKnapsackSolutionAnalyzer.BinaryVectorParameter.ActualName = SolutionCreator.BinaryVectorParameter.ActualName;
308      BestKnapsackSolutionAnalyzer.BinaryVectorParameter.Hidden = true;
309      BestKnapsackSolutionAnalyzer.KnapsackCapacityParameter.ActualName = KnapsackCapacityParameter.Name;
310      BestKnapsackSolutionAnalyzer.KnapsackCapacityParameter.Hidden = true;
311      BestKnapsackSolutionAnalyzer.WeightsParameter.ActualName = WeightsParameter.Name;
312      BestKnapsackSolutionAnalyzer.WeightsParameter.Hidden = true;
313      BestKnapsackSolutionAnalyzer.ValuesParameter.ActualName = ValuesParameter.Name;
314      BestKnapsackSolutionAnalyzer.ValuesParameter.Hidden = true;
315    }
316    private void InitializeOperators() {
317      operators = new List<IOperator>();
318      operators.Add(new BestKnapsackSolutionAnalyzer());
319      ParameterizeAnalyzer();
320      foreach (IBinaryVectorOperator op in ApplicationManager.Manager.GetInstances<IBinaryVectorOperator>()) {
321        if (!(op is ISingleObjectiveMoveEvaluator) || (op is IKnapsackMoveEvaluator)) {
322          operators.Add(op);
323        }
324      }
325      ParameterizeOperators();
326      InitializeMoveGenerators();
327    }
328    private void InitializeMoveGenerators() {
329      foreach (IOneBitflipMoveOperator op in Operators.OfType<IOneBitflipMoveOperator>()) {
330        if (op is IMoveGenerator) {
331          op.OneBitflipMoveParameter.ActualNameChanged += new EventHandler(OneBitflipMoveParameter_ActualNameChanged);
332        }
333      }
334    }
335    private void ParameterizeOperators() {
336      foreach (IBinaryVectorCrossover op in Operators.OfType<IBinaryVectorCrossover>()) {
337        op.ParentsParameter.ActualName = SolutionCreator.BinaryVectorParameter.ActualName;
338        op.ParentsParameter.Hidden = true;
339        op.ChildParameter.ActualName = SolutionCreator.BinaryVectorParameter.ActualName;
340        op.ChildParameter.Hidden = true;
341      }
342      foreach (IBinaryVectorManipulator op in Operators.OfType<IBinaryVectorManipulator>()) {
343        op.BinaryVectorParameter.ActualName = SolutionCreator.BinaryVectorParameter.ActualName;
344        op.BinaryVectorParameter.Hidden = true;
345      }
346      foreach (IBinaryVectorMoveOperator op in Operators.OfType<IBinaryVectorMoveOperator>()) {
347        op.BinaryVectorParameter.ActualName = SolutionCreator.BinaryVectorParameter.ActualName;
348        op.BinaryVectorParameter.Hidden = true;
349      }
350      foreach (IKnapsackMoveEvaluator op in Operators.OfType<IKnapsackMoveEvaluator>()) {
351        op.KnapsackCapacityParameter.ActualName = KnapsackCapacityParameter.Name;
352        op.KnapsackCapacityParameter.Hidden = true;
353        op.PenaltyParameter.ActualName = PenaltyParameter.Name;
354        op.PenaltyParameter.Hidden = true;
355        op.WeightsParameter.ActualName = WeightsParameter.Name;
356        op.WeightsParameter.Hidden = true;
357        op.ValuesParameter.ActualName = ValuesParameter.Name;
358        op.ValuesParameter.Hidden = true;
359      }
360      foreach (var op in Operators.OfType<IBinaryVectorMultiNeighborhoodShakingOperator>()) {
361        op.BinaryVectorParameter.ActualName = SolutionCreator.BinaryVectorParameter.ActualName;
362        op.BinaryVectorParameter.Hidden = true;
363      }
364    }
365    #endregion
366
367    private void InitializeRandomKnapsackInstance() {
368      System.Random rand = new System.Random();
369
370      int itemCount = rand.Next(10, 100);
371      Weights = new IntArray(itemCount);
372      Values = new IntArray(itemCount);
373
374      double totalWeight = 0;
375
376      for (int i = 0; i < itemCount; i++) {
377        int value = rand.Next(1, 10);
378        int weight = rand.Next(1, 10);
379
380        Values[i] = value;
381        Weights[i] = weight;
382        totalWeight += weight;
383      }
384
385      int capacity = (int)Math.Round(0.7 * totalWeight);
386      KnapsackCapacity = new IntValue(capacity);
387    }
388  }
389}
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