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); }