inline virtual std::string run(const Dataset& train, const Dataset& test)
{
srand(time(NULL));
initialize_pop(train, test);
std::pair<unsigned int, double> best_at_train;
for (unsigned int i = 0; i < num_iter; ++i)
{
std::cout << "--- ITERATION " << i + 1 << " ---" << std::endl;
iteration(train, test);
best_at_train = cur_pop->best(train);
std::vector<Statistics> fitness_train = cur_pop->evaluate(train);
std::cout << "RMSE (train): " << fitness_train[best_at_train.first].rmse << std::endl;
std::cout << "MSE (train): " << fitness_train[best_at_train.first].mse << std::endl;
std::cout << "MAE (train): " << fitness_train[best_at_train.first].mae << std::endl;
std::cout << "Total error (train): " << fitness_train[best_at_train.first].total_error << std::endl;
std::vector<Statistics> fitness_test = cur_pop->evaluate(test, false);
std::cout << "RMSE (test): " << fitness_test[best_at_train.first].rmse << std::endl;
std::cout << "MSE (test): " << fitness_test[best_at_train.first].mse << std::endl;
std::cout << "MAE (test): " << fitness_test[best_at_train.first].mae << std::endl;
std::cout << "Total error (test): " << fitness_test[best_at_train.first].total_error << std::endl;
std::cout << "Size: " << (*cur_pop)[best_at_train.first].size() << std::endl;
}
return graph->print_expression((*cur_pop)[best_at_train.first].get_index());
}
/*Algoritmo Principal*/
int main(int argc, char *argv[])
{
char name[20];// = "_kita_1";
char archiveName[20] = "archive";
char fitputName[20] = "fitput";
char varputName[20] = "varput";
char hvName[20]= "hv";
unsigned int i, j, t;
unsigned int fun, gen;
clock_t startTime, endTime;
double duration, clocktime;
FILE *fitfile,*varfile;
/*Parametros iniciales*/
strcpy(name,argv[1]);
fun = atoi(argv[2]);
gen = atoi(argv[3]);
printf("%s %d %d \n",name,fun,gen);
initialize_data(fun,gen);
/*Iniciar variables*/
initialize_memory();
/*
sprintf(name,"kita_1_");
sprintf(archiveName,strcat(name,"archive.out"));
sprintf(fitputName, strcat(name,"fitput.out"));
sprintf(varputName, strcat(name,"varput.out"));
sprintf(hvName,strcat(name,"hv.out"));
*/
//fitfile = fopen(strcat(strcat(fitputName,name),".out"),"w");
//varfile = fopen(strcat(strcat(varputName,name),".out"),"w");
//hv = fopen(strcat(strcat(hvName,name),".out"),"w");
/* Iniciar generador de aleatorios*/
initialize_rand();
startTime = clock();
/* Iniciar contador de generaciones*/
t = 0;
/* Iniciar valores de la poblacion de manera aleatoria*/
initialize_pop();
/* Calcular velocidad inicial*/
initialize_vel();
/* Evaluar las particulas de la poblacion*/
evaluate();
/* Almacenar el pBest inicial (variables and valor de aptitud) de las particulas*/
store_pbests();
/* Insertar las particulas no domindas de la poblacion en el archivo*/
insert_nondom();
//printf("\n%d",nondomCtr);
/*Ciclo Principal*/
while(t <= maxgen)
{
//clocktime = (clock() - startTime)/(double)CLOCKS_PER_SEC;
/*if(verbose > 0 && t%printevery==0 || t == maxgen)
{
fprintf(stdout,"Generation %d Time: %.2f sec\n",t,clocktime);
fflush(stdout);
}*/
/*if(t%printevery==0 || t == maxgen)
{
fprintf(outfile,"Generation %d Time: %.2f sec\n",t,clocktime);
}*/
/* Calcular la nueva velocidad de cada particula en la pooblacion*/
//printf("\n 1");
compute_velocity();
/* Calcular la nueva posicion de cada particula en la poblacion*/
//printf("\n 2");
compute_position();
/* Mantener las particulas en la poblacion de la poblacion en el espacio de busqueda*/
//printf("\n 3");
maintain_particles();
/* Pertubar las particulas en la poblacion*/
if(t < maxgen * pMut)
mutate(t);
/* Evaluar las particulas en la poblacion*/
//printf("\n 4");
evaluate();
/* Insertar nuevas particulas no domindas en el archivo*/
//printf("\n 5");
update_archive();
/* Actualizar el pBest de las particulas en la poblacion*/
//printf("\n 6");
update_pbests();
/* Escribir resultados del mejor hasta ahora*/
//verbose > 0 && t%printevery==0 || t == maxgen
/*if(t%printevery==0 || t == maxgen)
{
//fprintf(outfile, "Size of Pareto Set: %d\n", nondomCtr);
fprintf(fitfile, "%d\n",t);
fprintf(varfile, "%d\n",t);
for(i = 0; i < nondomCtr; i++)
{
for(j = 0; j < maxfun; j++)
fprintf(fitfile, "%f ", archiveFit[i][j]);
fprintf(fitfile, "\n");
}
fprintf(fitfile, "\n\n");
fflush(fitfile);
for(i = 0; i < nondomCtr; i++)
{
for(j = 0; j < maxfun; j++)
fprintf(varfile, "%f ", archiveVar[i][j]);
fprintf(varfile, "\n");
}
fprintf(varfile, "\n\n");
fflush(varfile);
}*/
/* Incrementar contador de generaciones*/
t++;
//printf("%d\n",t);
}
/* Escribir resultados en el archivo */
save_results(strcat(strcat(archiveName,name),".out"));
endTime = clock();
duration = ( endTime - startTime ) / (double)CLOCKS_PER_SEC;
fprintf(stdout, "%lf sec\n", duration);
//fclose(fitfile);
//fclose(varfile);
free_memory();
return EXIT_SUCCESS;
}
main(int argc, char *argv[])
{
/* Declare vars : */
/* - these for the getopt stuff... */
int c;
int lflg = 0, mflg = 0, errflg = 0;
extern char *optarg;
extern int optind, optopt;
/* - and these for the main program... */
int i , code_length, pop_size = 200, generations = 10, rand_seed = 123;
pop_member *head_of_pop;
/* figure out all the cmd line requests... */
while ((c = getopt(argc, argv, ":l:p:g:r:m")) != -1)
switch (c) {
case 'l':
lflg++;
code_length = atoi(optarg);
break;
case 'p':
pop_size = atoi(optarg);
break;
case 'g':
generations = atoi(optarg);
break;
case 'r':
rand_seed = atoi(optarg);
break;
case 'm':
mflg++;
break;
case ':': /* -l, -p, -g, or -r without arguments */
fprintf(stderr, "Option -%c requires an argument!\n", optopt);
errflg++;
break;
case '?':
fprintf(stderr, "Unrecognized option: -%c\n", optopt);
errflg++;
}
if (!lflg) errflg++;
if (errflg || argc == 1) {
fprintf(stderr, "usage: \n");
fprintf(stderr, " ga_codes -l <code_length> ");
fprintf(stderr, "[ -p <no. of pop members, default=200> ] \\ \n");
fprintf(stderr, " [ -g <no. of generations, default=10> ] \\ \n");
fprintf(stderr, " [ -r <integer random no. seed, default=123> ] \\ \n");
fprintf(stderr, " [ -m [for matlab compatible output] ]\n\n");
exit(2);
}
/* use random seed to initiate random number generator */
srand48(rand_seed);
/* initialize population with randomly generated codes */
head_of_pop = initialize_pop(pop_size, code_length);
/* evaluate population */
head_of_pop = apply_evals_to_pop(head_of_pop, code_length);
/* sort population by evals */
head_of_pop = sort_pop_by_evals(head_of_pop, code_length);
/* print out all codes and evals in pop for diagnostic use... */
/* printout_pop(head_of_pop, code_length); printf("\n"); */
/* loop thru iterations of reproduction and replacing pop members that
* have poor evals... */
for (i = 1; i <= generations; i++) {
/* run a reproduction cycle */
head_of_pop = next_generation(head_of_pop, pop_size, code_length);
/* evaluate population */
head_of_pop = apply_evals_to_pop(head_of_pop, code_length);
/* sort population by evals */
head_of_pop = sort_pop_by_evals(head_of_pop, code_length);
/* print out all codes and evals in pop for diagnostic use...
* printout_pop(head_of_pop, code_length); printf("\n"); */
}
/* print output info... */
printout_info(mflg, code_length, pop_size, generations, rand_seed,
head_of_pop->code, head_of_pop->eval,
head_of_pop->max_sl_height);
} /* end main */
int maintest (int argc, char **argv)
{
int i;
FILE *fpt1;
FILE *fpt2;
FILE *fpt3;
FILE *fpt4;
FILE *fpt5;
population *parent_pop;
population *child_pop;
population *mixed_pop;
int gnuplt= 1;
if (argc<2)
{
printf("\n Usage ./nsga2r random_seed \n");
exit(1);
}
seed = (double)atof(argv[1]);
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("initial_pop.out","w");
fpt2 = fopen("final_pop.out","w");
fpt3 = fopen("best_pop.out","w");
fpt4 = fopen("all_pop.out","w");
fpt5 = fopen("params.out","w");
fprintf(fpt1,"# This file contains the data of initial population\n");
fprintf(fpt2,"# This file contains the data of final population\n");
fprintf(fpt3,"# This file contains the data of final feasible population (if found)\n");
fprintf(fpt4,"# This file contains the data of all generations\n");
fprintf(fpt5,"# This file contains information about inputs as read by the program\n");
if(argc > 2) {
char *in_file_name = argv[2];
if (read_inputParam_from_file(in_file_name) < 0) exit(1);
gnuplt = 0;
}
else
if (read_inputParam() < 0) exit(1);
printf("\n Input data successfully entered, now performing initialization \n");
fprintf(fpt5,"\n Population size = %d",popsize);
fprintf(fpt5,"\n Number of generations = %d",ngen);
fprintf(fpt5,"\n Number of objective functions = %d",nobj);
fprintf(fpt5,"\n Number of constraints = %d",ncon);
fprintf(fpt5,"\n Number of real variables = %d",nreal);
if (nreal!=0)
{
for (i=0; i<nreal; i++)
{
fprintf(fpt5,"\n Lower limit of real variable %d = %e",i+1,min_realvar[i]);
fprintf(fpt5,"\n Upper limit of real variable %d = %e",i+1,max_realvar[i]);
}
fprintf(fpt5,"\n Probability of crossover of real variable = %e",pcross_real);
fprintf(fpt5,"\n Probability of mutation of real variable = %e",pmut_real);
fprintf(fpt5,"\n Distribution index for crossover = %e",eta_c);
fprintf(fpt5,"\n Distribution index for mutation = %e",eta_m);
}
fprintf(fpt5,"\n Number of binary variables = %d",nbin);
if (nbin!=0)
{
for (i=0; i<nbin; i++)
{
fprintf(fpt5,"\n Number of bits for binary variable %d = %d",i+1,nbits[i]);
fprintf(fpt5,"\n Lower limit of binary variable %d = %e",i+1,min_binvar[i]);
fprintf(fpt5,"\n Upper limit of binary variable %d = %e",i+1,max_binvar[i]);
}
fprintf(fpt5,"\n Probability of crossover of binary variable = %e",pcross_bin);
fprintf(fpt5,"\n Probability of mutation of binary variable = %e",pmut_bin);
}
fprintf(fpt5,"\n Seed for random number generator = %e",seed);
bitlength = 0;
if (nbin!=0)
{
for (i=0; i<nbin; i++)
{
bitlength += nbits[i];
}
}
fprintf(fpt1,"# of objectives = %d, # of constraints = %d, # of real_var = %d, # of bits of bin_var = %d, constr_violation, rank, crowding_distance\n",nobj,ncon,nreal,bitlength);
fprintf(fpt2,"# of objectives = %d, # of constraints = %d, # of real_var = %d, # of bits of bin_var = %d, constr_violation, rank, crowding_distance\n",nobj,ncon,nreal,bitlength);
fprintf(fpt3,"# of objectives = %d, # of constraints = %d, # of real_var = %d, # of bits of bin_var = %d, constr_violation, rank, crowding_distance\n",nobj,ncon,nreal,bitlength);
fprintf(fpt4,"# of objectives = %d, # of constraints = %d, # of real_var = %d, # of bits of bin_var = %d, constr_violation, rank, crowding_distance\n",nobj,ncon,nreal,bitlength);
nbinmut = 0;
nrealmut = 0;
nbincross = 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");
decode_pop(parent_pop);
evaluate_pop (parent_pop);
assign_rank_and_crowding_distance (parent_pop);
report_pop (parent_pop, fpt1);
fprintf(fpt4,"# gen = 1\n");
report_pop(parent_pop,fpt4);
printf("\n gen = 1");
fflush(stdout);
if (choice!=0) {
if(gnuplt) onthefly_display (parent_pop,gp,1);
else display (parent_pop,1);
}
fflush(fpt1);
fflush(fpt2);
fflush(fpt3);
fflush(fpt4);
fflush(fpt5);
_sleep(1);
for (i=2; i<=ngen; i++)
{
selection (parent_pop, child_pop);
mutation_pop (child_pop);
decode_pop(child_pop);
evaluate_pop(child_pop);
merge (parent_pop, child_pop, mixed_pop);
fill_nondominated_sort (mixed_pop, parent_pop);
/* Comment following four lines if information for all
generations is not desired, it will speed up the execution */
fprintf(fpt4,"# gen = %d\n",i);
report_pop(parent_pop,fpt4);
fflush(fpt4);
if (choice!=0) {
if(gnuplt) onthefly_display (parent_pop,gp,i);
else display (parent_pop,i);
}
printf("\n gen = %d",i);
}
printf("\n Generations finished, now reporting solutions");
report_pop(parent_pop,fpt2);
report_feasible(parent_pop,fpt3);
if (nreal!=0)
{
fprintf(fpt5,"\n Number of crossover of real variable = %d",nrealcross);
fprintf(fpt5,"\n Number of mutation of real variable = %d",nrealmut);
}
if (nbin!=0)
{
fprintf(fpt5,"\n Number of crossover of binary variable = %d",nbincross);
fprintf(fpt5,"\n Number of mutation of binary variable = %d",nbinmut);
}
fflush(stdout);
fflush(fpt1);
fflush(fpt2);
fflush(fpt3);
fflush(fpt4);
fflush(fpt5);
fclose(fpt1);
fclose(fpt2);
fclose(fpt3);
fclose(fpt4);
fclose(fpt5);
if (choice!=0 && gnuplt)
{
_pclose(gp);
}
if (nreal!=0)
{
free (min_realvar);
free (max_realvar);
}
if (nbin!=0)
{
free (min_binvar);
free (max_binvar);
free (nbits);
}
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);
}
/* -------------------------------------------------------------------------------
* NSGA2
* ---------------------------------------------------------------------------- */
int nsga2(int nvar, int ncon, int nobj, double f[], double x[], double g[],
int nfeval, double xl[], double xu[], int popsize, int ngen,
double pcross_real, double pmut_real, double eta_c, double eta_m,
double pcross_bin, double pmut_bin, int printout, double seed)
{
/* declaration of local variables and structures */
int i, j;
int nreal, nbin, *nbits, bitlength;
double *min_realvar, *max_realvar;
double *min_binvar, *max_binvar;
int *nbinmut, *nrealmut, *nbincross, *nrealcross;
Global global;
population *parent_pop;
population *child_pop;
population *mixed_pop;
// "random" numbers seed
if (seed==0)
{
// use of clock to generate "random" seed
time_t seconds;
seconds=time(NULL);
seed=seconds;
}
// Files
FILE *fpt1;
FILE *fpt2;
FILE *fpt3;
FILE *fpt4;
FILE *fpt5;
FILE *fpt6;
if (printout >= 1)
{
fpt1 = fopen("nsga2_initial_pop.out","w");
fpt2 = fopen("nsga2_final_pop.out","w");
fpt3 = fopen("nsga2_best_pop.out","w");
if (printout == 2)
{
fpt4 = fopen("nsga2_all_pop.out","w");
}
fpt5 = fopen("nsga2_params.out","w");
fpt6 = fopen("nsga2_run.out","w");
fprintf(fpt1,"# This file contains the data of initial population\n");
fprintf(fpt2,"# This file contains the data of final population\n");
fprintf(fpt3,"# This file contains the data of final feasible population (if found)\n");
if (printout == 2)
{
fprintf(fpt4,"# This file contains the data of all generations\n");
}
fprintf(fpt5,"# This file contains information about inputs as read by the program\n");
fprintf(fpt6,"# This file contains runtime information\n");
}
// Input Handling
nreal = nvar; // number of real variables
nbin = 0; // number of binary variables
min_realvar = (double *)malloc(nreal*sizeof(double));
max_realvar = (double *)malloc(nreal*sizeof(double));
j = 0;
for (i=0; i<nvar; i++)
{
min_realvar[j] = xl[i];
max_realvar[j] = xu[i];
j += 1;
}
if (nbin != 0)
{
nbits = (int *)malloc(nbin*sizeof(int));
min_binvar = (double *)malloc(nbin*sizeof(double));
max_binvar = (double *)malloc(nbin*sizeof(double));
}
bitlength = 0;
if (nbin!=0)
{
for (i=0; i<nbin; i++)
{
bitlength += nbits[i];
}
}
// Performing Initialization
if (printout >= 1)
{
fprintf(fpt5,"\n Population size = %d",popsize);
fprintf(fpt5,"\n Number of generations = %d",ngen);
fprintf(fpt5,"\n Number of objective functions = %d",nobj);
fprintf(fpt5,"\n Number of constraints = %d",ncon);
fprintf(fpt5,"\n Number of variables = %d",nvar);
fprintf(fpt5,"\n Number of real variables = %d",nreal);
if (nreal!=0)
{
for (i=0; i<nreal; i++)
{
fprintf(fpt5,"\n Lower limit of real variable %d = %e",i+1,min_realvar[i]);
fprintf(fpt5,"\n Upper limit of real variable %d = %e",i+1,max_realvar[i]);
}
fprintf(fpt5,"\n Probability of crossover of real variable = %e",pcross_real);
fprintf(fpt5,"\n Probability of mutation of real variable = %e",pmut_real);
fprintf(fpt5,"\n Distribution index for crossover = %e",eta_c);
fprintf(fpt5,"\n Distribution index for mutation = %e",eta_m);
}
fprintf(fpt5,"\n Number of binary variables = %d",nbin);
if (nbin!=0)
{
for (i=0; i<nbin; i++)
{
fprintf(fpt5,"\n Number of bits for binary variable %d = %d",i+1,nbits[i]);
fprintf(fpt5,"\n Lower limit of binary variable %d = %e",i+1,min_binvar[i]);
fprintf(fpt5,"\n Upper limit of binary variable %d = %e",i+1,max_binvar[i]);
}
fprintf(fpt5,"\n Probability of crossover of binary variable = %e",pcross_bin);
fprintf(fpt5,"\n Probability of mutation of binary variable = %e",pmut_bin);
}
fprintf(fpt5,"\n Seed for random number generator = %e",seed);
fprintf(fpt1,"# of objectives = %d, # of constraints = %d, # of real_var = %d, # of bits of bin_var = %d, constr_violation, rank, crowding_distance\n",nobj,ncon,nreal,bitlength);
fprintf(fpt2,"# of objectives = %d, # of constraints = %d, # of real_var = %d, # of bits of bin_var = %d, constr_violation, rank, crowding_distance\n",nobj,ncon,nreal,bitlength);
fprintf(fpt3,"# of objectives = %d, # of constraints = %d, # of real_var = %d, # of bits of bin_var = %d, constr_violation, rank, crowding_distance\n",nobj,ncon,nreal,bitlength);
if (printout == 2)
{
fprintf(fpt4,"# of objectives = %d, # of constraints = %d, # of real_var = %d, # of bits of bin_var = %d, constr_violation, rank, crowding_distance\n",nobj,ncon,nreal,bitlength);
}
}
//
global.nreal = nreal;
global.nbin = nbin;
global.nobj = nobj;
global.ncon = ncon;
global.popsize = popsize;
global.pcross_real = pcross_real;
global.pcross_bin = pcross_bin;
global.pmut_real = pmut_real;
global.pmut_bin = pmut_bin;
global.eta_c = eta_c;
global.eta_m = eta_m;
global.ngen = ngen;
global.nbits = nbits;
global.min_realvar = min_realvar;
global.max_realvar = max_realvar;
global.min_binvar = min_binvar;
global.max_binvar = max_binvar;
global.bitlength = bitlength;
//
nbinmut = 0;
nrealmut = 0;
nbincross = 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, global);
allocate_memory_pop (child_pop, popsize, global);
allocate_memory_pop (mixed_pop, 2*popsize, global);
randomize();
initialize_pop (parent_pop, global);
// First Generation
if (printout >= 1)
{
fprintf(fpt6,"\n\n Initialization done, now performing first generation");
}
decode_pop(parent_pop, global);
evaluate_pop(parent_pop, global);
assign_rank_and_crowding_distance (parent_pop, global);
if (printout >= 1)
{
report_pop (parent_pop, fpt1, global);
if (printout == 2)
{
fprintf(fpt4,"# gen = 1\n");
report_pop(parent_pop,fpt4, global);
}
fprintf(fpt6,"\n gen = 1");
fflush(fpt1);
fflush(fpt2);
fflush(fpt3);
if (printout == 2)
{
fflush(fpt4);
}
fflush(fpt5);
fflush(fpt6);
}
fflush(stdout);
// Iterate Generations
for (i=2; i<=ngen; i++)
{
selection(parent_pop, child_pop, global, nrealcross, nbincross);
mutation_pop(child_pop, global, nrealmut, nbinmut);
decode_pop(child_pop, global);
evaluate_pop(child_pop, global);
merge (parent_pop, child_pop, mixed_pop, global);
fill_nondominated_sort (mixed_pop, parent_pop, global);
/* Comment following three lines if information for all
generations is not desired, it will speed up the execution */
if (printout >= 1)
{
if (printout == 2)
{
fprintf(fpt4,"# gen = %i\n",i);
report_pop(parent_pop,fpt4, global);
fflush(fpt4);
}
fprintf(fpt6,"\n gen = %i",i);
fflush(fpt6);
}
}
// Output
if (printout >= 1)
{
fprintf(fpt6,"\n Generations finished");
report_pop(parent_pop,fpt2, global);
report_feasible(parent_pop,fpt3, global);
if (nreal!=0)
{
fprintf(fpt5,"\n Number of crossover of real variable = %i",nrealcross);
fprintf(fpt5,"\n Number of mutation of real variable = %i",nrealmut);
}
if (nbin!=0)
{
fprintf(fpt5,"\n Number of crossover of binary variable = %i",nbincross);
fprintf(fpt5,"\n Number of mutation of binary variable = %i",nbinmut);
}
fflush(stdout);
fflush(fpt1);
fflush(fpt2);
fflush(fpt3);
if (printout == 2)
{
fflush(fpt4);
}
fflush(fpt5);
fflush(fpt6);
fclose(fpt1);
fclose(fpt2);
fclose(fpt3);
if (printout == 2)
{
fclose(fpt4);
}
fclose(fpt5);
}
//
for (i=0; i<popsize; i++)
{
if (parent_pop->ind[i].constr_violation == 0.0 && parent_pop->ind[i].rank==1)
{
for (j=0; j<nobj; j++)
{
f[j] = parent_pop->ind[i].obj[j];
}
if (ncon!=0)
{
for (j=0; j<ncon; j++)
{
g[j] = parent_pop->ind[i].constr[j];
}
}
if (nreal!=0)
{
for (j=0; j<nreal; j++)
{
x[j] = parent_pop->ind[i].xreal[j];
}
}
break;
}
}
//
if (nreal!=0)
{
free (min_realvar);
free (max_realvar);
}
if (nbin!=0)
{
free (min_binvar);
free (max_binvar);
free (nbits);
}
deallocate_memory_pop (parent_pop, popsize, global);
deallocate_memory_pop (child_pop, popsize, global);
deallocate_memory_pop (mixed_pop, 2*popsize, global);
free (parent_pop);
free (child_pop);
free (mixed_pop);
//
if (printout >= 1)
{
fprintf(fpt6,"\n Routine successfully exited \n");
fflush(fpt6);
fclose(fpt6);
}
return (0);
}
int main (int argc, char **argv)
{
int i;
FILE *fpt1;
FILE *fpt2;
FILE *fpt3;
FILE *fpt4;
FILE *fpt5;
population *parent_pop;
population *child_pop;
population *mixed_pop;
fpt1 = fopen("output/initial_pop.out","w");
fpt2 = fopen("output/final_pop.out","w");
fpt3 = fopen("output/best_pop.out","w");
fpt4 = fopen("output/all_pop.out","w");
fpt5 = fopen("output/params.out","w");
fprintf(fpt1,"# This file contains the data of initial population\n");
fprintf(fpt2,"# This file contains the data of final population\n");
fprintf(fpt3,"# This file contains the data of final feasible population (if found)\n");
fprintf(fpt4,"# This file contains the data of all generations\n");
fprintf(fpt5,"# This file contains information about inputs as read by the program\n");
// 读取执行参数
read_run_param();
if (seed<=0.0 || seed>=1.0)
{
printf("\n Entered seed value is wrong, seed value must be in (0,1) \n");
exit(1);
}
// printf("\n Enter the problem relevant and algorithm relevant parameters ... ");
// printf("\n Enter the population size (a multiple of 4) : ");
// scanf("%d",&popsize);
if (popsize<4 || (popsize%4)!= 0)
{
printf("\n population size read is : %d",popsize);
printf("\n Wrong population size entered, hence exiting \n");
exit (1);
}
// printf("\n Enter the number of generations : ");
// scanf("%d",&ngen);
if (ngen<1)
{
printf("\n number of generations read is : %d",ngen);
printf("\n Wrong nuber of generations entered, hence exiting \n");
exit (1);
}
// printf("\n Enter the number of objectives : ");
// scanf("%d",&nobj);
if (nobj<1)
{
printf("\n number of objectives entered is : %d",nobj);
printf("\n Wrong number of objectives entered, hence exiting \n");
exit (1);
}
// printf("\n Enter the number of constraints : ");
// scanf("%d",&ncon);
if (ncon<0)
{
printf("\n number of constraints entered is : %d",ncon);
printf("\n Wrong number of constraints enetered, hence exiting \n");
exit (1);
}
// printf("\n Enter the number of real variables : ");
// scanf("%d",&nreal);
if (nreal<0)
{
printf("\n number of real variables entered is : %d",nreal);
printf("\n Wrong number of variables entered, hence exiting \n");
exit (1);
}
if (nreal != 0)
{
min_realvar = (double *)malloc(nreal*sizeof(double));
max_realvar = (double *)malloc(nreal*sizeof(double));
for (i=0; i<nreal; i++)
{
// printf ("\n Enter the lower limit of real variable %d : ",i+1);
// scanf ("%lf",&min_realvar[i]);
// printf ("\n Enter the upper limit of real variable %d : ",i+1);
// scanf ("%lf",&max_realvar[i]);
max_realvar[i] = 1;
min_realvar[i] = 0;
if (max_realvar[i] <= min_realvar[i])
{
printf("\n Wrong limits entered for the min and max bounds of real variable, hence exiting \n");
exit(1);
}
}
// printf ("\n Enter the probability of crossover of real variable (0.6-1.0) : ");
// scanf ("%lf",&pcross_real);
if (pcross_real<0.0 || pcross_real>1.0)
{
printf("\n Probability of crossover entered is : %e",pcross_real);
printf("\n Entered value of probability of crossover of real variables is out of bounds, hence exiting \n");
exit (1);
}
// printf ("\n Enter the probablity of mutation of real variables (1/nreal) : ");
// scanf ("%lf",&pmut_real);
if (pmut_real<0.0 || pmut_real>1.0)
{
printf("\n Probability of mutation entered is : %e",pmut_real);
printf("\n Entered value of probability of mutation of real variables is out of bounds, hence exiting \n");
exit (1);
}
// printf ("\n Enter the value of distribution index for crossover (5-20): ");
// scanf ("%lf",&eta_c);
if (eta_c<=0)
{
printf("\n The value entered is : %e",eta_c);
printf("\n Wrong value of distribution index for crossover entered, hence exiting \n");
exit (1);
}
// printf ("\n Enter the value of distribution index for mutation (5-50): ");
// scanf ("%lf",&eta_m);
if (eta_m<=0)
{
printf("\n The value entered is : %e",eta_m);
printf("\n Wrong value of distribution index for mutation entered, hence exiting \n");
exit (1);
}
}
// printf("\n Enter the number of binary variables : ");
// scanf("%d",&nbin);
if (nbin<0)
{
printf ("\n number of binary variables entered is : %d",nbin);
printf ("\n Wrong number of binary variables entered, hence exiting \n");
exit(1);
}
if (nbin != 0)
{
nbits = (int *)malloc(nbin*sizeof(int));
min_binvar = (double *)malloc(nbin*sizeof(double));
max_binvar = (double *)malloc(nbin*sizeof(double));
for (i=0; i<nbin; i++)
{
// printf ("\n Enter the number of bits for binary variable %d : ",i+1);
// scanf ("%d",&nbits[i]);
if (nbits[i] < 1)
{
printf("\n Wrong number of bits for binary variable entered, hence exiting");
exit(1);
}
// printf ("\n Enter the lower limit of binary variable %d : ",i+1);
// scanf ("%lf",&min_binvar[i]);
// printf ("\n Enter the upper limit of binary variable %d : ",i+1);
// scanf ("%lf",&max_binvar[i]);
max_binvar[i] = 1;
min_binvar[i] = 0;
if (max_binvar[i] <= min_binvar[i])
{
printf("\n Wrong limits entered for the min and max bounds of binary variable entered, hence exiting \n");
exit(1);
}
}
// printf ("\n Enter the probability of crossover of binary variable (0.6-1.0): ");
// scanf ("%lf",&pcross_bin);
pcross_bin = 0.8;
if (pcross_bin<0.0 || pcross_bin>1.0)
{
printf("\n Probability of crossover entered is : %e",pcross_bin);
printf("\n Entered value of probability of crossover of binary variables is out of bounds, hence exiting \n");
exit (1);
}
// printf ("\n Enter the probability of mutation of binary variables (1/nbits): ");
// scanf ("%lf",&pmut_bin);
pmut_bin = 0.02;
if (pmut_bin<0.0 || pmut_bin>1.0)
{
printf("\n Probability of mutation entered is : %e",pmut_bin);
printf("\n Entered value of probability of mutation of binary variables is out of bounds, hence exiting \n");
exit (1);
}
}
if (nreal==0 && nbin==0)
{
printf("\n Number of real as well as binary variables, both are zero, hence exiting \n");
exit(1);
}
choice=0;
printf(" Input data successfully entered, now performing initialization \n");
fprintf(fpt5,"\n Population size = %d",popsize);
fprintf(fpt5,"\n Number of generations = %d",ngen);
fprintf(fpt5,"\n Number of objective functions = %d",nobj);
fprintf(fpt5,"\n Number of constraints = %d",ncon);
fprintf(fpt5,"\n Number of real variables = %d",nreal);
if (nreal!=0)
{
for (i=0; i<nreal; i++)
{
fprintf(fpt5,"\n Lower limit of real variable %d = %e",i+1,min_realvar[i]);
fprintf(fpt5,"\n Upper limit of real variable %d = %e",i+1,max_realvar[i]);
}
fprintf(fpt5,"\n Probability of crossover of real variable = %e",pcross_real);
fprintf(fpt5,"\n Probability of mutation of real variable = %e",pmut_real);
fprintf(fpt5,"\n Distribution index for crossover = %e",eta_c);
fprintf(fpt5,"\n Distribution index for mutation = %e",eta_m);
}
fprintf(fpt5,"\n Number of binary variables = %d",nbin);
if (nbin!=0)
{
for (i=0; i<nbin; i++)
{
fprintf(fpt5,"\n Number of bits for binary variable %d = %d",i+1,nbits[i]);
fprintf(fpt5,"\n Lower limit of binary variable %d = %e",i+1,min_binvar[i]);
fprintf(fpt5,"\n Upper limit of binary variable %d = %e",i+1,max_binvar[i]);
}
fprintf(fpt5,"\n Probability of crossover of binary variable = %e",pcross_bin);
fprintf(fpt5,"\n Probability of mutation of binary variable = %e",pmut_bin);
}
fprintf(fpt5,"\n Seed for random number generator = %e",seed);
bitlength = 0;
if (nbin!=0)
{
for (i=0; i<nbin; i++)
{
bitlength += nbits[i];
}
}
fprintf(fpt1,"# of objectives = %d, # of constraints = %d, # of real_var = %d, # of bits of bin_var = %d, constr_violation, rank, crowding_distance\n",nobj,ncon,nreal,bitlength);
fprintf(fpt2,"# of objectives = %d, # of constraints = %d, # of real_var = %d, # of bits of bin_var = %d, constr_violation, rank, crowding_distance\n",nobj,ncon,nreal,bitlength);
fprintf(fpt3,"# of objectives = %d, # of constraints = %d, # of real_var = %d, # of bits of bin_var = %d, constr_violation, rank, crowding_distance\n",nobj,ncon,nreal,bitlength);
fprintf(fpt4,"# of objectives = %d, # of constraints = %d, # of real_var = %d, # of bits of bin_var = %d, constr_violation, rank, crowding_distance\n",nobj,ncon,nreal,bitlength);
nbinmut = 0;
nrealmut = 0;
nbincross = 0;
nrealcross = 0;
// 读取问题参数
read_prob_param();
// 根据参数申请空间
allocate_prob();
// 输入问题
input_prob();
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(" Initialization done, now performing first generation\n");
decode_pop(parent_pop);
evaluate_pop (parent_pop);
assign_rank_and_crowding_distance (parent_pop);
report_pop (parent_pop, fpt1);
fprintf(fpt4,"# gen = 1\n");
report_pop(parent_pop,fpt4);
printf("gen = 1\n");
fflush(stdout);
fflush(fpt1);
fflush(fpt2);
fflush(fpt3);
fflush(fpt4);
fflush(fpt5);
//sleep(1);
for (i=2; i<=ngen; i++)
{
selection (parent_pop, child_pop);
mutation_pop (child_pop);
decode_pop(child_pop);
evaluate_pop(child_pop);
merge (parent_pop, child_pop, mixed_pop);
fill_nondominated_sort (mixed_pop, parent_pop);
/* Comment following four lines if information for all
generations is not desired, it will speed up the execution */
fprintf(fpt4,"# gen = %d\n",i);
report_pop(parent_pop,fpt4);
fflush(fpt4);
printf("gen = %d\n",i);
}
printf(" Generations finished, now reporting solutions\n");
report_pop(parent_pop,fpt2);
report_feasible(parent_pop,fpt3);
// 输出 task
FILE *fpt_task;
fpt_task = fopen("output/task_pop.out", "w");
report_pop_task(parent_pop, fpt_task);
fclose(fpt_task);
if (nreal!=0)
{
fprintf(fpt5,"\n Number of crossover of real variable = %d",nrealcross);
fprintf(fpt5,"\n Number of mutation of real variable = %d",nrealmut);
}
if (nbin!=0)
{
fprintf(fpt5,"\n Number of crossover of binary variable = %d",nbincross);
fprintf(fpt5,"\n Number of mutation of binary variable = %d",nbinmut);
}
fflush(stdout);
fflush(fpt1);
fflush(fpt2);
fflush(fpt3);
fflush(fpt4);
fflush(fpt5);
fclose(fpt1);
fclose(fpt2);
fclose(fpt3);
fclose(fpt4);
fclose(fpt5);
if (nreal!=0)
{
free (min_realvar);
free (max_realvar);
}
if (nbin!=0)
{
free (min_binvar);
free (max_binvar);
free (nbits);
}
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);
// 释放问题申请的空间
deallocate_prob();
printf(" Routine successfully exited \n");
return (0);
}