improved-particle-swarm-algorithm.rar_swarm_改进粒子群

function [xm,fv] = SecVibratPSO(fitness,N,w,c1,c2,M,D) format long; %------初始化种群的个体------------ for i=1:N for j=1:D x(i,j)=randn; %随机初始化位置 xl(i,j)=randn; v(i,j)=randn; %随机初始化速度 end end %------先计算各个粒子的适应度，并初始化Pi和Pg---------------------- for i=1:N p(i)=fitness(x(i,:)); y(i,:)=x(i,:); end pg = x(N,:); %Pg为全局最优 for i=1:(N-1) if fitness(x(i,:))<fitness(pg) pg=x(i,:); end end %------进入主要循环，按照公式依次迭代------------ for t=1:M for i=1:N phi1 = c1*rand(); phi2 = c2*rand(); if t < M/2 ks1 = (2*sqrt(phi1)-1)*rand()/phi1; ks2 = (2*sqrt(phi2)-1)*rand()/phi2; else ks1 = (2*sqrt(phi1)-1)*(1 + rand())/phi1; ks2 = (2*sqrt(phi2)-1)*(1 + rand())/phi2; end v(i,:)=w*v(i,:)+phi1*(y(i,:)-(1+ks1)*x(i,:)+ks1*xl(i,:))+ ... phi2*(pg-(1+ks2)*x(i,:)+ks1*xl(i,:)); xl(i,:) = x(i,:); x(i,:)=x(i,:)+v(i,:); if fitness(x(i,:))<p(i) p(i)=fitness(x(i,:)); y(i,:)=x(i,:); end if p(i)<fitness(pg) pg=y(i,:); end end Pbest(t)=fitness(pg); end xm = pg'; fv = fitness(pg);