dmain.cpp

多目标优化进化算法目前公认效果收敛性最好的算法NSGA2c++源码,具有一般性

///////////////////////////////////////////////////////////////////
/*****************************************************************
Copyright: Artificial Life and Adaptive Robotics Laboratory - ALAR
School of ITEE, UNSW@ADFA, Australia, 2005
*******************************************************************/
///////////////////////////////////////////////////////////////////


#include "operators_NSGA2.h"

int main(int argc, char* argv[])
{
	
	double dev=0;
	
	int i,select=1;
	int N = 100;  // populations
	int GEN = 200;  // generation
	int SEED = 1050;	 
	double pc=0.15,pm=0.06;
	int objID=1;
	
	int NObjs=2;            // number of objectives
	
	int NGenes=30;            // number of genes in the chromosome
	int *GSize; // length of each gene
	double *Ub; // upper bounds of gene-variables
	double *Lb; // lower bounds of gene-variables
	
	
	// threshold and number of non-dominated solutions or archive fixed size	
	int alpha=20;			
	
	
	if (argc != 8)
	{
		cout << endl << endl;
		cout << "There should be 7 parameters                 " << endl;
		cout << "-----------------------------                 " << endl;
		cout << "01- population_size                           " << endl;
		cout << "02- number_of_genes                           " << endl;
		cout << "03- number_of_generations                     " << endl;
		cout << "04- Number_of_objectives                      " << endl;
		cout << "05- Objective_number                          " << endl;
		cout << "06- start SEED  " << endl;
		cout << "07- end SEED  " << endl;
		
		exit(1);
	}
	
	// Pass the parameters
	
	N      = atoi(argv[1]);
	NGenes = atoi(argv[2]);
	GEN    = atoi(argv[3]);
	NObjs  = atoi(argv[4]);
	objID  = atoi(argv[5]);
	int ss = atoi(argv[6]);
	int es = atoi(argv[7]);
	
	
	//
	if (objID==5) NGenes=11;    
	if (objID==6) NGenes=10;    
	if (objID==4) NGenes=10;    
	if (objID>=7) NGenes=5;    
	
	GSize = new int[NGenes];    // length of each gene
	
	Ub=new double[NGenes];   // upper bounds of gene-variables
	Lb=new double[NGenes];	
	
	// For Dynammic testing: only problems: 7,8,9,10,11,12
	for (i=0;i<NGenes;i++)
	{
		if (objID==5)
		{
			if (i==0)
				GSize[i]=30;
			else
				GSize[i]=5;
		} else
			GSize[i]=30;
		
		if (objID==4)
		{
			if (i==0)
			{Ub[i]=1; Lb[i]=0;}
			else
			{Ub[i]=5; Lb[i]=-5;}
		}
		else if ((objID>=7)&&(objID<=12))
		{
			Ub[i]=100; Lb[i]=0;
		}
		else
		{
			Ub[i]=1; Lb[i]=0;
		}
	}
	
	
	operators_NSGA2 opNSGA2(pc,pm,objID);
	int j;
	
	for (SEED=ss;SEED<=es;SEED=SEED+10)
	{
		for (i=50;i<=100;i=i+5)
		{
			for (j=0;j<=20;j++)
			{
				pc    = (double)i/100.0;
				pm    = (double)j/100.0;
				opNSGA2.init(pc,pm,objID);
				opNSGA2.Evolve(N,GEN,SEED,NGenes,NObjs,GSize,Ub,Lb); 
			}
		}
	}
	return 0; 
}