1  #region License Information


2  /* HeuristicLab


3  * Copyright (C) 20022015 Joseph Helm and 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 


23  using HeuristicLab.Core;


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


25  using HeuristicLab.Data;


26  using HeuristicLab.Common;


27  using HeuristicLab.Encodings.PackingEncoding;


28 


29  namespace HeuristicLab.Problems.BinPacking {


30  [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")]


31  [StorableClass]


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


33  where D : class, IPackingPosition


34  where B : PackingShape<D>


35  where I : PackingShape<D>, IPackingItem {


36 


37  [StorableConstructor]


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


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


40  : base(original, cloner) {


41  }


42  public PackingRatioRegularIdenticalBinEvaluator() : base() { }


43 


44  protected override DoubleValue Evaluate() {


45  DoubleValue quality = new DoubleValue(0);


46 


47  IPackingPlan plan = PackingPlanParameter.ActualValue;


48  B binMeasure = PackingBinMeasuresParameter.ActualValue;


49  ItemList<I> itemMeasures = PackingItemMeasuresParameter.ActualValue;


50 


51 


52  //Check if data is valid


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


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


55 


56 


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


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


59 


60 


61 


62  //if (itemPositionsAreValid)


63  return CalculatePackingRatio(plan as PackingPlan<D, B, I>);


64 


65  //return quality;


66  }


67 


68  /*


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


70 


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


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


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


74  C.......the bin capacity and


75  k.......a constant, k>1.


76  */


77  public static DoubleValue CalculatePackingRatio(PackingPlan<D, B, I> plan) {


78  int nrOfBins = plan.NrOfBins;


79  double result = 0;


80 


81  //C


82  //double usableSpace = binMeasure.MultipliedMeasures;


83  //nrOfBins = N


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


85  //C


86  //double usableSpace = plan.GetPackingBinMeasuresForBinNr(0).MultipliedMeasures;//plan.GetPackingBinMeasuresForBinNr(i).MultipliedMeasures;


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


88  //var packedItemsInThisBin = plan.PackingItemMeasures.Select((Value, Index) => new { Value, Index }).Where(s => indexes.Contains(s.Index));


89  //Fi


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


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


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


93  var PD = plan.BinPackings[i].PackingDensity;


94  result += (PD * PD) / (i + 1);


95  }


96 


97  result = result / nrOfBins;


98  return new DoubleValue(result);


99  }


100  }


101  }

