* =====================================================================================
*
* Filename: particle.c
*
* Description:
*
* Version: 1.0
* Created: 2012年03月17日 15时27分13秒
* Revision: none
* Compiler: gcc
*
* Author: MaZheng (blog.csdn.net/mazheng19), mazheng191019@gmail.com
* Company: Dalian University Of Technology
*
* =====================================================================================
*/
//粒子群PSO算法
#include #include #include #include #definePI 3.1415926535/* */ #define P_num 200 //粒子数目 #define dim 50 #define low -100 //搜索域范围 #define high 100 #define iter_num 1000 #define V_max 20 //速度范围 #define c1 2 #define c2 2 #define w 0.5 #define alp 1 double particle[P_num][dim]; //个体集合 double particle_loc_best[P_num][dim]; //每个个体局部最优向量 double particle_loc_fit[P_num]; //个体的局部最优适应度,有局部最优向量计算而来 double particle_glo_best[dim]; //全局最优向量 double gfit; //全局最优适应度,有全局最优向量计算而来 double particle_v[P_num][dim]; //记录每个个体的当前代速度向量 double particle_fit[P_num]; //记录每个粒子的当前代适应度 double Sphere(double a[]) { int i; double sum=0.0; for(i=0; i sum+=a[i]*a[i]; } return sum; } double Rosenbrock(double a[]) { int i; double sum=0.0; for(i=0;i sum+= 100*(a[i+1]-a[i]*a[i])*(a[i+1]-a[i]*a[i])+(a[i]-1)*(a[i]-1); } return sum; } double Rastrigin(double a[]) { int i; double sum=0.0; for(i=0;i sum+=a[i]*a[i]-10.0*cos(2*PI*a[i])+10.0; } return sum; } double fitness(double a[]) //适应度函数 { return Rastrigin(a); } void initial() { int i,j; for(i=0; i for(j=0; j particle[i][j] = low+(high-low)*1.0*rand()/RAND_MAX; //初始化群体 particle_loc_best[i][j] = particle[i][j]; //将当前最优结果写入局部最优集合 particle_v[i][j] = -V_max+2*V_max*1.0*rand()/RAND_MAX; //速度 } } for(i=0; i particle_fit[i] = fitness(particle[i]); particle_loc_fit[i] = particle_fit[i]; } gfit = particle_loc_fit[0]; //找出全局最优 j=0; for(i=1; i if(particle_loc_fit[i] gfit = particle_loc_fit[i]; j = i; } } for(i=0; i particle_glo_best[i] = particle_loc_best[j][i]; } } void renew_particle() { int i,j; for(i=0; i for(j=0; j particle[i][j] += alp*particle_v[i][j]; if(particle[i][j] > high) { parti cle[i][j] = high; } if(particle[i][j] < low) { particle[i][j] = low; } } } } void renew_var() { int i, j; for(i=0; i particle_fit[i] = fitness(particle[i]); if(particle_fit[i] < particle_loc_fit[i]) //更新个体局部最优值 { particle_loc_fit[i] = particle_fit[i]; for(j=0; j particle_loc_best[i][j] = particle[i][j]; } } } for(i=0,j=-1; i if(particle_loc_fit[i] gfit = particle_loc_fit[i]; j = i; } } if(j != -1) { for(i=0; i particle_glo_best[i] = particle_loc_best[j][i]; } } for(i=0; i for(j=0; j particle_v[i][j]=w*particle_v[i][j]+ c1*1.0*rand()/RAND_MAX*(particle_loc_best[i][j]-particle[i][j])+ c2*1.0*rand()/RAND_MAX*(particle_glo_best[j]-particle[i][j]); if(particle_v[i][j] > V_max) { particle_v[i][j] = V_max; } if(particle_v[i][j] < -V_max) { particle_v[i][j] = -V_max; } } } } int main() { freopen("result.txt下载本文
