nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/behavior/DEGTBehavior.java

   1 /**
   2  * Description: The description of differential evolution Generate-and-Test Behavior.
   3
   4   #Supported parameters:
   5   NAME    VALUE_type   Range      DefaultV        Description
   6   FACTOR   real        (0, 1.2]   0.5             DEAgent: scale constant
   7   CR       real        [0, 1]     0.9             DEAgent: crossover constant
   8   //Other choices for FACTOR and CR: (0.5, 0.1)
   9
  10  *
  11  * Author          Create/Modi     Note
  12  * Xiaofeng Xie    May 11, 2004
  13  * Xiaofeng Xie    Jul 01, 2008
  14  *
  15  * @version 1.0
  16  * @Since MAOS1.0
  17  *
  18  * @References:
  19  * [1] Storn R, Price K. Differential evolution - a simple and efficient
  20  *     heuristic for global optimization over continuous spaces. Journal of
  21  *     Global Optimization, 1997, 11: 341-359
  22  *     The original differential evolution idea
  23  * [2] X F Xie, W J Zhang. SWAF: swarm algorithm framework for numerical
  24  *     optimization. Genetic and Evolutionary Computation Conference (GECCO),
  25  *     Seattle, WA, USA, 2004: 238-250
  26  *     -> a generate-and-test behavior
  27  */
  28
  29 package net.adaptivebox.deps.behavior;
  30
  31 import net.adaptivebox.global.RandomGenerator;
  32 import net.adaptivebox.goodness.IGoodnessCompareEngine;
  33 import net.adaptivebox.knowledge.Library;
  34 import net.adaptivebox.knowledge.SearchPoint;
  35 import net.adaptivebox.problem.ProblemEncoder;
  36 import net.adaptivebox.space.BasicPoint;
  37
  38 public class DEGTBehavior extends AbsGTBehavior {
  39   //Number of differential vectors, normally be 1 or 2
  40   private static final int DVNum = 2;
  41
  42   //scale constant: (0, 1.2], normally be 0.5
  43   public double MIN_FACTOR = 0.5;
  44
  45   //scale constant: (0, 1.2], normally be 0.5
  46   public double MAX_FACTOR = 0.5;
  47
  48   //crossover constant: [0, 1], normally be 0.1 or 0.9
  49   public double CR = 0.9;
  50
  51   @Override
  52   public void setMemPoints(SearchPoint pbest, BasicPoint pcurrent, BasicPoint pold) {
  53     pbest_t = pbest;
  54   }
  55
  56   /**
  57    * Crossover and mutation for a single vector element done in a single step.
  58    *
  59    * @param index             Index of the trial vector element to be changed.
  60    * @param trialVector       Trial vector reference.
  61    * @param globalVector      Global best found vector reference.
  62    * @param differenceVectors List of vectors used for difference delta
  63    *                          calculation.
  64    */
  65   private void crossoverAndMutation(int index, double trialVector[], double globalVector[],
  66       BasicPoint differenceVectors[]) {
  67     double delta = 0D;
  68
  69     for (int i = 0; i < differenceVectors.length; i++) {
  70       delta += (i % 2 == 0 ? +1D : -1D) * differenceVectors[i].getLocation()[index];
  71     }
  72
  73     trialVector[index] = globalVector[index] + RandomGenerator.doubleRangeRandom(MIN_FACTOR, MAX_FACTOR) * delta;
  74   }
  75
  76   @Override
  77   public void generateBehavior(SearchPoint trailPoint, ProblemEncoder problemEncoder) {
  78     BasicPoint[] referPoints = getReferPoints();
  79     int DIMENSION = problemEncoder.getDesignSpace().getDimension();
  80     int guaranteeIndex = RandomGenerator.intRangeRandom(0, DIMENSION - 1);
  81
  82     double[] trailVector = trailPoint.getLocation();
  83     double[] locaclVector = pbest_t.getLocation();
  84     double[] globalVector = socialLib.getGbest().getLocation();
  85
  86     /* Handle first part of the trial vector. */
  87     for (int index = 0; index < guaranteeIndex; index++) {
  88       if (CR <= RandomGenerator.doubleZeroOneRandom()) {
  89         trailVector[index] = locaclVector[index];
  90         continue;
  91       }
  92
  93       crossoverAndMutation(index, trailVector, globalVector, referPoints);
  94     }
  95
  96     /* Guarantee for at least one change in the trial vector. */
  97     crossoverAndMutation(guaranteeIndex, trailVector, globalVector, referPoints);
  98
  99     /* Handle second part of the trial vector. */
 100     for (int index = guaranteeIndex + 1; index < DIMENSION; index++) {
 101       if (CR <= RandomGenerator.doubleZeroOneRandom()) {
 102         trailVector[index] = locaclVector[index];
 103         continue;
 104       }
 105
 106       crossoverAndMutation(index, trailVector, globalVector, referPoints);
 107     }
 108   }
 109
 110   @Override
 111   public void testBehavior(SearchPoint trailPoint, IGoodnessCompareEngine qualityComparator) {
 112     Library.replace(qualityComparator, trailPoint, pbest_t);
 113   }
 114
 115   private SearchPoint[] getReferPoints() {
 116     SearchPoint[] referPoints = new SearchPoint[DVNum * 2];
 117     for (int i = 0; i < referPoints.length; i++) {
 118       referPoints[i] = socialLib.getRandomPoint();
 119     }
 120     return referPoints;
 121   }
 122 }