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/**
* Description: For comparison of goodness in landscape with loosed constraints
* which varied adaptively according to the social information.
*
* @Applied domain: efficiently for ridge class feasible space (SF), such as
* the problem with eqaulity constraints
*
* @ Author Create/Modi Note
* Xiaofeng Xie Jun 24, 2003 Created
* Xiaofeng Xie May 11, 2004
*
* This library is free software; you can redistribute it and/or
* modify it under the terms of the GNU Lesser General Public
* License as published by the Free Software Foundation; either
* version 2.1 of the License, or (at your option) any later version.
*
* This library is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* Lesser General Public License for more details.
*
* Please acknowledge the author(s) if you use this code in any way.
*
* @version 1.0
* @Since MAOS1.2
*
* [1] Xie X F, Zhang W J, Bi D C. Handling equality constraints by adaptive
* relaxing rule for swarm algorithms. Congress on Evolutionary Computation,
* Oregon, USA, 2004
*/
package net.adaptivebox.goodness;
import net.adaptivebox.knowledge.*;
import net.adaptivebox.global.*;
public class ACRComparator implements IGoodnessCompareEngine, IUpdateCycleEngine {
private Library socialPool;
private double epsilon_t = 0;
private double RU = 0.75;
private double RL = 0.25;
private double BETAF = 0.618;
private double BETAL = 0.618;
private double BETAU = 1.382;
private double T = -1;
private double TthR = 0.5;
public ACRComparator(Library lib, int T) {
socialPool = lib;
this.T = T;
//set the (epsilon_t|t=0) as the maximum CONS value among the SearchPoints in the library
epsilon_t = lib.getExtremalVcon(true);
}
static public int compare(double data1, double data2) {
if (data1 < data2)
return LESS_THAN;
else if (data1 > data2)
return LARGER_THAN;
else
return EQUAL_TO;
}
public int compare(double[] fit1, double[] fit2) {
if(Math.max(fit1[0], fit2[0])<=Math.max(0, epsilon_t)) { //epsilon>0
return compare(fit1[1], fit2[1]);
} else {
return compare(fit1[0], fit2[0]);
}
}
public void updateCycle(int t) {
//calculates the ratio
double rn = (double)socialPool.getVconThanNum(epsilon_t)/(double)socialPool.getPopSize();
if(t>TthR*T &&T!=-1) { //Forcing sub-rule
epsilon_t *= BETAF;
} else { //Ratio-keeping sub-rules
if(rn>RU) {
epsilon_t *= BETAL; //Shrink
}
if(rn<RL) {
epsilon_t *= BETAU; //Relax
}
}
}
}
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