1  #region License Information


2  /* HeuristicLab


3  * Copyright (C) 20022012 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 


22  using System;


23  using System.Collections.Generic;


24  using System.Linq;


25  using System.Text;


26  using HeuristicLab.Core;


27  using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;


28  using HeuristicLab.Problems.BinPacking.Interfaces;


29  using HeuristicLab.Problems.BinPacking.Shapes;


30  using HeuristicLab.Data;


31  using HeuristicLab.Common;


32  using HeuristicLab.Problems.BinPacking.PackingPlans;


33 


34  namespace HeuristicLab.Problems.BinPacking.Evaluators {


35  [Item("PackingRatio Regular IdenticalBin Evaluator", "Represents an evaluationalgorithm for regularshaped binpacking problems with identical bins which calculates the ratio between packed and unpacked space. Found in Falkenauer:1996")]


36  [StorableClass]


37  public abstract class PackingRatioRegularIdenticalBinEvaluator<D, B, I> : RegularSimpleRotationIdenticalBinPackingPlanEvaluator<D, B, I>


38  where D : class, IPackingDimensions


39  where B : PackingShape<D>, IPackingBin, IRegularPackingShape


40  where I : PackingShape<D>, IPackingItem, IRegularPackingShape {


41 


42  [StorableConstructor]


43  protected PackingRatioRegularIdenticalBinEvaluator(bool deserializing) : base(deserializing) { }


44  protected PackingRatioRegularIdenticalBinEvaluator(PackingRatioRegularIdenticalBinEvaluator<D, B, I> original, Cloner cloner)


45  : base(original, cloner) {


46  }


47  public PackingRatioRegularIdenticalBinEvaluator() : base() { }


48 


49  protected override DoubleValue Evaluate() {


50  DoubleValue quality = new DoubleValue(0);


51 


52  IPackingPlan plan = PackingPlanParameter.ActualValue;


53  B binMeasure = PackingBinMeasuresParameter.ActualValue;


54  ItemList<I> itemMeasures = PackingItemMeasuresParameter.ActualValue;


55  int nrOfBins = plan.NrOfBins;


56 


57 


58  //Check if data is valid


59  //if (plan.PackingItemPositions.Count != itemMeasures.Count)


60  // throw new Exception("ERROR: ItemMeasures.count does not match packingPosition.count");


61 


62 


63  ////Check if any items are overlapping or not contained in their bins


64  //bool itemPositionsAreValid = !HasOverlappingOrNotContainedItems(plan.PackingItemPositions, binMeasure, itemMeasures, nrOfBins);


65 


66 


67 


68  //if (itemPositionsAreValid)


69  return CalculatePackingRatio(plan as PackingPlan<D, B, I>, binMeasure, itemMeasures, nrOfBins);


70 


71  //return quality;


72  }


73 


74  /*


75  Falkenauer:1996  A Hybrid Grouping Genetic Algorithm for Bin Packing


76 


77  fBPP = (SUM[i=1..N](Fi / C)^k)/N


78  N.......the number of bins used in the solution,


79  Fi......the sum of sizes of the items in the bin i (the fill of the bin),


80  C.......the bin capacity and


81  k.......a constant, k>1.


82  */


83  private DoubleValue CalculatePackingRatio(PackingPlan<D, B, I> plan, B binMeasure, ItemList<I> itemMeasures, int nrOfBins) {


84  double result = 0;


85 


86  //C


87  double usableSpace = binMeasure.MultipliedMeasures;


88  //nrOfBins = N


89  for (int i = 0; i < nrOfBins; i++) {


90  var indexes = plan.PackingItemPositions.Select((Value, Index) => new { Value, Index }).Where(s => s.Value.Value.AssignedBin == i).Select(s => s.Index);


91  var packedItemsInThisBin = itemMeasures.Select((Value, Index) => new { Value, Index }).Where(s => indexes.Contains(s.Index));


92  //Fi


93  double usedSpaceInThisBin = packedItemsInThisBin.Select(s => s.Value.MultipliedMeasures).Sum();


94  //k = 2 > (Fi/C)*(Fi/C)


95  result += (((usedSpaceInThisBin) / (usableSpace)) * ((usedSpaceInThisBin) / (usableSpace))) / (i + 1);


96  }


97 


98  result = result / nrOfBins;


99  return new DoubleValue (result);


100  }


101  }


102  }

