sharingscaling.cpp

我自己写的一个用于图编码的遗传算法

#include "SharingScaling.h"

void SharingScaling::applyScaling(Population* pop)
{
	//if(p.size() > (int)N)
	//{
	//	delete [] d;
	//	N = p.size();
	//	d = new float[N*N];
	//}
	//int n = p.size();

	//int i, j;
	//if(df) 
	//{
	//	for(i=0; i<n; i++)
	//	{		// calculate and cache the distances
	//		d[i*n+i] = 0.0;		// each genome is same as itself
	//		for(j=i+1; j<n; j++)
	//			d[i*n+j] = d[j*n+i] = (*df)(p.individual(i), p.individual(j));
	//	}
	//}
	//else
	//{
	//	for(i=0; i<n; i++){		// calculate and cache the distances
	//		d[i*n+i] = 0.0;		// each genome is same as itself
	//		for(j=i+1; j<n; j++)
	//			d[i*n+j] = d[j*n+i] = p.individual(i).compare(p.individual(j));
	//	}
	//}

	//int mm;
	//if(_minmax == 0)
	//{
	//	if(p.geneticAlgorithm())
	//		mm = p.geneticAlgorithm()->minimaxi();
	//	else
	//		mm = ((p.order() == GAPopulation::HIGH_IS_BEST) ? 
	//		GAGeneticAlgorithm::MAXIMIZE : GAGeneticAlgorithm::MINIMIZE);
	//}
	//else
	//{
	//	mm = _minmax;
	//}

	//for(i=0; i<n; i++)
	//{		// now derate the fitness of each genome
	//	double sum = 0.0;
	//	for(j=0; j<n; j++) 
	//	{
	//		if(d[i*n+j] < _sigma)
	//		{
	//			if(_alpha == 1)
	//				sum += ((d[i*n+j] >= _sigma) ? 0.0 : 1.0 - d[i*n+j]/_sigma);
	//			else
	//				sum += ((d[i*n+j]>=_sigma) ? 0.0 : 1.0-pow(d[i*n+j]/_sigma,_alpha));
	//		}
	//	}
	//	double f;
	//	if(mm == GAGeneticAlgorithm::MINIMIZE)
	//		f = p.individual(i).score() * sum;
	//	else
	//		f = p.individual(i).score() / sum;
	//	p.individual(i).fitness((float)f);       // might lose information here!
	//}
}