pso.rar_PSO_pso最小值_www.37pso.com_粒子群算法

close all;clear all;clc; %% ======To find the minimum value========= % 基本粒子群算法程序完成 N=30; % the number of population D=30; %dimension xmin(1:D)=-10; %minimum value xmax(1:D)=10; %maximum value c1=0.9; c2=1.0; w=0.9; %------------初始化(方法1)------------- for i=1:N for j=1:D x(i,j)=xmin(j)+(xmax(j)-xmin(j))*rand; end end %--------初始适应度值的计算---------- for i=1:N x_fit(i,:)=fitness(x(i,:)); end v=rand(N,D); x_pbest=x; % the current best x_gbest(1,:)=x(find(x_fit==min(x_fit)),:);% the global best Tmax=100;%最大迭代次数 %迭代更新过程=========== for t=1:Tmax t for i=1:N v(i,:)=w*v(i,:)+c1*rand*(x_pbest(i,:)-x(i,:))+c2*rand*(x_gbest(t,:)-x(i,:)); x(i,:)=x(i,:)+v(i,:); x_fit1(i,:)=fitness(x(i,:)); if x_fit1(i,:)<x_fit(i,:) x_pbest(i,:)=x(i,:); end x_fit(i,:)=fitness(x(i,:)); end x_gbest(t+1,:)=x(find(x_fit==min(x_fit)),:); Fitmin(t,:)=min(x_fit); Fitmean(t,:)=mean(x_fit); end figure(1) plot(1:Tmax,Fitmin,'r',1:Tmax,Fitmean,'b') legend('最小值','平均值')