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.goodness.*;
  32 import net.adaptivebox.global.*;
  33 import net.adaptivebox.knowledge.*;
  34 import net.adaptivebox.problem.*;
  35 import net.adaptivebox.space.*;
  36
  37 public class DEGTBehavior extends AbsGTBehavior implements ILibEngine {
  38   public int DVNum = 2;  //Number of differential vectors, normally be 1 or 2
  39   public double FACTOR = 0.5; //scale constant: (0, 1.2], normally be 0.5
  40   public double CR = 0.9;     //crossover constant: [0, 1], normally be 0.1 or 0.9
  41
  42   //the own memory: store the point that generated in last learning cycle
  43   protected SearchPoint pbest_t;
  44
  45   public void setPbest(SearchPoint pbest) {
  46     pbest_t = pbest;
  47   }
  48
  49   public void generateBehavior(SearchPoint trailPoint, ProblemEncoder problemEncoder) {
  50     SearchPoint gbest_t = socialLib.getGbest();
  51
  52     BasicPoint[] referPoints = getReferPoints();
  53     int DIMENSION = problemEncoder.getDesignSpace().getDimension();
  54     int rj = RandomGenerator.intRangeRandom(0, DIMENSION-1);
  55     for (int k=0; k<DIMENSION; k++) {
  56       if (Math.random()<CR || k == DIMENSION-1) {
  57         double Dabcd = 0;
  58         for(int i=0; i<referPoints.length; i++) {
  59           Dabcd += Math.pow(-1, i%2)*referPoints[i].getLocation()[rj];
  60         }
  61         trailPoint.getLocation()[rj] = gbest_t.getLocation()[rj]+FACTOR*Dabcd;
  62       } else {
  63         trailPoint.getLocation()[rj] = pbest_t.getLocation()[rj];
  64       }
  65       rj = (rj+1)%DIMENSION;
  66     }
  67   }
  68
  69   public void testBehavior(SearchPoint trailPoint, IGoodnessCompareEngine qualityComparator) {
  70     Library.replace(qualityComparator, trailPoint, pbest_t);
  71   }
  72
  73   protected SearchPoint[] getReferPoints() {
  74     SearchPoint[] referPoints = new SearchPoint[DVNum*2];
  75     for(int i=0; i<referPoints.length; i++) {
  76       referPoints[i] = socialLib.getSelectedPoint(RandomGenerator.intRangeRandom(0, socialLib.getPopSize()-1));
  77     }
  78     return referPoints;
  79   }
  80 }
  81