多目标粒子群算法C代码

/************************************************************************* * This is an implementation of MOPSO-CD,a multiobjective particle swarm * * optimization algorithm using crowding distance * * * * For details please see: * * C.R. Raquel and P.C. Naval, Jr., An Effective Use of Crowding * * Distance in Multiobjective Particle Swarm Optimization. * * In Proc. of Genetic and Evolutionary Computation Conference * * (GECCO 2005), Washington DC, June 2005. * * * * E-mail address : cvmig@engg.upd.edu.ph * * Version : mopsocd05b * * Last updated : Fri Feb 17, 2006 * * * * Random Generator Source code has been taken from Random Library found * * at http://www.swin.edu.au/astronomy/pbourke/software/random/ * * * * Permission to use MOPSO-CD codes is hereby granted for academic and * * research purposes only. Commercial usage of these codes is prohibited * * without prior knowledge of the authors. In no way will the authors * * be held responsible for any possible faulty operation of * * software/hardware arising from the use of these codes. * *************************************************************************/ /************************************************* FUNCTION CODE OPTIMIZATION OBJECTIVE VARIABLES Kita 100 maximize (1) 2 2 Kursawe 200 minimize (0) 2 3 Deb 300 minimize (0) 2 2 DTLZ6 500 minimize (0) 3 22 <- put yours here and in test-fun.h /* Initialize your function in initialize_pop() */ /* Put your function in evaluate() */ /* Put your constraints, if any, in check_constraints(...) */ /* See also maintain_particles() routine */ /**************************************************/ #define function 500 /* set functions code */ #define popsize 100 /* set number of particles in the population */ #define maxgen 1000 /* set maximum number of generations */ #define optimization 0 /* set optimization type, 0 for min, 1 for max */ #define archive_size 500 /* set capacity of archive */ #define maxfun 3 /* set maximum number of objective functions */ #define maxvar 22 /* set maximum number of variables */ #define verbose 1 /* verbosity level 0,1 */ #define printevery 10 /* how frequently should output be generated */ #include <stdlib.h> #include <stdio.h> #include <string.h> #include <math.h> #include <time.h> #include "randomlib.h" double PI; void initialize_rand(void); void initialize_pop(void); void initialize_vel(void); void evaluate(void); double kita_f1(unsigned int); double kita_f2(unsigned int); double kursawe_f1(unsigned int); double kursawe_f2(unsigned int); double deb_f1(unsigned int); double deb_f2(unsigned int); void store_pbests(void); void insert_nondom(void); void delete_particle(unsigned int); unsigned int compare_particles(unsigned int, unsigned int); unsigned int check_constraints(double *); void crowding(void); void qsortFitness(unsigned int, unsigned int, unsigned int); void qsortCrowd(unsigned int, unsigned int); void compute_distance(unsigned int); void mutate(unsigned int); void get_ranges(double *, double *); void maintain_particles(void); void compute_velocity(void); void update_archive(void); unsigned int check_nondom(unsigned int); void update_pbests(void); void save_results(char *); double DTLZ6_f1(unsigned int); double DTLZ6_f2(unsigned int); double DTLZ6_f3(unsigned int); double archiveVar[archive_size][maxvar]; /* variable values of particles in the archive */ double archiveFit[archive_size][maxfun]; /* fitness values of particles in the archive */ double popVar[popsize][maxvar]; /* variable values of particles in the population */ double popFit[popsize][maxfun]; /* fitness values of particles in the population */ double pbestsVar[popsize][maxvar]; /* personal bests of particles in the population */ double pbestsFit[popsize][maxfun]; /* personal bests of particles in the population */ double velocity[popsize][maxvar]; /* velocity of particles in the population */ double crowdDist[archive_size]; /* crowding distance values of particles in archive */ double pMut=0.5; /* probability of mutation */ unsigned int nondomCtr = 0; /* number of nondominated solutions in archive */ int main(int argc, char *argv[]) { char archiveName[20]; unsigned int i, j, t; clock_t startTime, endTime; double duration, clocktime; FILE *outfile,*plotfile; PI = 4.0*atan(1.0); sprintf(archiveName,"archive.out"); outfile = fopen("output.out","w"); plotfile = fopen("plot.out","w"); /* Initialize random number generator */ initialize_rand(); startTime = clock(); /* Initialize generation counter */ t = 0; /* Initialize population with random values */ initialize_pop(); /* Initialize velocity */ initialize_vel(); /* Evaluate particles in population */ evaluate(); /* Store initial personal bests (both variable and fitness values) of particles */ store_pbests(); /* Insert nondominated particles in population into the archive */ insert_nondom(); /******* MAIN LOOP *********/ 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); } /* Compute crowding distance of each particle in the archive */ /* Only when there are at least 3 particles in the archive */ if(nondomCtr > 2) crowding(); /* Compute new velocity of each particle in the population */ compute_velocity(); /* Maintain particles in the population within the search space */ maintain_particles(); /* Mutate particles in the population */ if(t < maxgen * pMut) mutate(t); /* Evaluate particles in the population */ evaluate(); /* Insert new nondominated particles in pop into archive */ update_archive(); /* Update personal bests of particles in the population */ update_pbests(); /* Print Best So Far */ if(t%printevery==0 || t == maxgen) { fprintf(outfile, "Size of Pareto Set: %d\n", nondomCtr); for(i = 0; i < nondomCtr; i++) { fprintf(outfile, "Function Values: "); for(j = 0; j < maxfun; j++) fprintf(outfile, "%.6f ", archiveFit[i][j]); fprintf(outfile, "\n"); for(j = 0; j < maxvar; j++) fprintf(outfile, "%.6f ", archiveVar[i][j]); fprintf(outfile, "\n"); } fprintf(outfile, "\n\n"); fflush(outfile); } if(t == maxgen) { fprintf(plotfile, "# GNU Plot\n"); for(i = 0; i < nondomCtr; i++) { for(j = 0; j < maxfun; j++) fprintf(plotfile, "%.4f ", archiveFit[i][j]); fprintf(plotfile, "\n"); } fflush(plotfile); } /* Increment generation counter */ t++; } /* Write results to file */ save_results(archiveName); /* Compute time duration */