source: branches/HeuristicLab.BinPacking/HeuristicLab.Problems.BinPacking/3.3/Evaluators/Abstract/PackingRatioRegularIdenticalBinEvaluator.cs @ 13365

#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2015 Joseph Helm and Heuristic and Evolutionary Algorithms Laboratory (HEAL)
 *
 * This file is part of HeuristicLab.
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 * HeuristicLab is free software: you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
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 * You should have received a copy of the GNU General Public License
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#endregion


using HeuristicLab.Core;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Problems.BinPacking.Interfaces;
using HeuristicLab.Problems.BinPacking.Shapes;
using HeuristicLab.Data;
using HeuristicLab.Common;
using HeuristicLab.Encodings.PackingEncoding.PackingPlan;

namespace HeuristicLab.Problems.BinPacking.Evaluators {
  [Item("Packing-Ratio Regular Identical-Bin Evaluator", "Represents an evaluation-algorithm for regular-shaped bin-packing problems with identical bins which calculates the ratio between packed and unpacked space. Found in Falkenauer:1996")]
  [StorableClass]
  public abstract class PackingRatioRegularIdenticalBinEvaluator<D, B, I> : RegularSimpleRotationIdenticalBinPackingPlanEvaluator<D, B, I>
    where D : class, IPackingDimensions
    where B : PackingShape<D>, IPackingBin, IRegularPackingShape
    where I : PackingShape<D>, IPackingItem, IRegularPackingShape {

    [StorableConstructor]
    protected PackingRatioRegularIdenticalBinEvaluator(bool deserializing) : base(deserializing) { }
    protected PackingRatioRegularIdenticalBinEvaluator(PackingRatioRegularIdenticalBinEvaluator<D, B, I> original, Cloner cloner)
      : base(original, cloner) {
    }
    public PackingRatioRegularIdenticalBinEvaluator() : base() { }

    protected override DoubleValue Evaluate() {
      DoubleValue quality = new DoubleValue(0);

      IPackingPlan plan = PackingPlanParameter.ActualValue;
      B binMeasure = PackingBinMeasuresParameter.ActualValue;
      ItemList<I> itemMeasures = PackingItemMeasuresParameter.ActualValue;


      //Check if data is valid
      //if (plan.PackingItemPositions.Count != itemMeasures.Count)
      //  throw new Exception("ERROR: ItemMeasures.count does not match packingPosition.count");


      ////Check if any items are overlapping or not contained in their bins
      //bool itemPositionsAreValid = !HasOverlappingOrNotContainedItems(plan.PackingItemPositions, binMeasure, itemMeasures, nrOfBins);



      //if (itemPositionsAreValid)
      return CalculatePackingRatio(plan as PackingPlan<D, B, I>);

      //return quality;
    }

    /* 
        Falkenauer:1996 - A Hybrid Grouping Genetic Algorithm for Bin Packing
        
        fBPP = (SUM[i=1..N](Fi / C)^k)/N
        N.......the number of bins used in the solution,
        Fi......the sum of sizes of the items in the bin i (the fill of the bin),
        C.......the bin capacity and
        k.......a constant, k>1.
     */
    public static DoubleValue CalculatePackingRatio(PackingPlan<D, B, I> plan) {
      int nrOfBins = plan.NrOfBins;
      double result = 0;

      //C
      //double usableSpace = binMeasure.MultipliedMeasures;
      //nrOfBins = N
      for (int i = 0; i < nrOfBins; i++) {
        //C
        //double usableSpace = plan.GetPackingBinMeasuresForBinNr(0).MultipliedMeasures;//plan.GetPackingBinMeasuresForBinNr(i).MultipliedMeasures;
        //var indexes = plan.PackingItemPositions.Select((Value, Index) => new { Value, Index }).Where(s => s.Value.Value.AssignedBin == i).Select(s => s.Index);
        //var packedItemsInThisBin = plan.PackingItemMeasures.Select((Value, Index) => new { Value, Index }).Where(s => indexes.Contains(s.Index));
        //Fi
        //double usedSpaceInThisBin = packedItemsInThisBin.Select(s => s.Value.MultipliedMeasures).Sum();
        //k = 2 --> (Fi/C)*(Fi/C)
        //result += (((usedSpaceInThisBin) / (usableSpace)) * ((usedSpaceInThisBin) / (usableSpace))) / (i*i + 1);
        var PD = plan.BinPackings[i].PackingDensity;
        result += (PD * PD) / (i + 1);
      }

      result = result / nrOfBins;
      return new DoubleValue (result);
    }
  }
}