nsga2r.c

多目标遗传算法的程序

/* NSGA-II routine (implementation of the 'main' function) */

# include <stdio.h>
# include <stdlib.h>
# include <math.h>
# include "time.h"

# include "global.h"
# include "rand.h"

int nreal;
int nobj;
int ncon;
int popsize;
long double pcross_real;
long double pmut_real;
long double eta_c;
long double eta_m;
int ngen;
int nrealmut;
int nrealcross;
int *nbits;
long double *min_realvar;
long double *max_realvar;
int main (int argc, char **argv)
{
    int i;
    FILE *fpt1;
    FILE *fpt2;
    FILE *fpt3;
    FILE *fpt4;
    FILE *fpt5;
	FILE *fpt6;
    population *parent_pop;
    population *child_pop;
    population *mixed_pop;
	int random;
    /*if (argc<2)
    {
        printf("\n Usage ./nsga2r random_seed \n");
        exit(1);
    }
    seed = (long double)atof(argv[1]);*/
	srand( (unsigned)time( NULL ) ); 
	random = rand()%1000;
    seed=(float) random/1000.0;
    if (seed<=0.0 || seed>=1.0)
    {
        printf("\n Entered seed value is wrong, seed value must be in (0,1) \n");
        exit(1);
    }
    fpt1 = fopen("初始种群.txt","w");
    fpt2 = fopen("最终种群.txt","w");
    fpt3 = fopen("pareto最优解(best_pop).txt","w");
    //fpt4 = fopen("all_pop.out","w");
    fpt5 = fopen("参数设置.txt","w");
	fpt6 = fopen("中间代最优解.txt","w");

	popsize=500;  
	ngen=500;  
	nobj=3; 
	ncon=4;
	nreal=2; 
	
    if (nreal != 0)
    {
        min_realvar = (long double *)malloc(nreal*sizeof(long double)); /* 用于存储相对应实数变量的下限 */
        max_realvar = (long double *)malloc(nreal*sizeof(long double)); /* 用于存储相对应实数变量的上限 */
//        for (i=0; i<nreal; i++)
//        {
//			min_realvar[i]=0.0; 
//			max_realvar[i]=1.0; 			 	
//         }
		min_realvar[0]=94000.0; 
		max_realvar[0]=104000.0; 
		min_realvar[1]=9901.0; 
		max_realvar[1]=12272.0;
		pcross_real=0.9; 
		pmut_real=0.1; 	
		eta_c=10; 
		eta_m=10; 
    }

    nrealmut = 0;
    nrealcross = 0;
    parent_pop = (population *)malloc(sizeof(population));
    child_pop = (population *)malloc(sizeof(population));
    mixed_pop = (population *)malloc(sizeof(population));
    allocate_memory_pop (parent_pop, popsize);
    allocate_memory_pop (child_pop, popsize);
    allocate_memory_pop (mixed_pop, 2*popsize);
    randomize();
    initialize_pop (parent_pop);
    printf("\n Initialization done, now performing first generation");

    evaluate_pop (parent_pop);
    assign_rank_and_crowding_distance (parent_pop);
    report_pop (parent_pop, fpt1);

    printf("\n 正在进化第  1  代......");
    fflush(stdout);
    fflush(fpt1);
    fflush(fpt2);
    fflush(fpt3);
    //fflush(fpt4);
    fflush(fpt5);
    for (i=2; i<=ngen; i++)
    {
        selection (parent_pop, child_pop);
        mutation_pop (child_pop);
        evaluate_pop(child_pop);
        merge (parent_pop, child_pop, mixed_pop);
        fill_nondominated_sort (mixed_pop, parent_pop);	
        printf("\n 正在进化第  %d  代......",i);
    }
    printf("\n Generations finished, now reporting solutions");
    report_pop(parent_pop,fpt2);
    report_feasible(parent_pop,fpt3);
	report_orginal (parent_pop, fpt6);

    fflush(stdout);
    fflush(fpt1);
    fflush(fpt2);
    fflush(fpt3);
    //fflush(fpt4);
    fflush(fpt5);
	fflush(fpt6);
    fclose(fpt1);
    fclose(fpt2);
    fclose(fpt3);
    //fclose(fpt4);
    fclose(fpt5);
	fclose(fpt6);
    if (nreal!=0)
    {
        free (min_realvar);
        free (max_realvar);
    }
    deallocate_memory_pop (parent_pop, popsize);
    deallocate_memory_pop (child_pop, popsize);
    deallocate_memory_pop (mixed_pop, 2*popsize);
    free (parent_pop);
    free (child_pop);
    free (mixed_pop);
    printf("\n Routine successfully exited \n");
    return (0);
}