PSO.m

% Particle Swarm Optimization
function [gBestScore,gBest,cg_curve]=PSO(noP,Max_iter,lb,ub,dim,fobj,da)


%PSO Infotmation

Vmax=ones(1,dim).*(ub-lb).*0.15;           %速度最大值

w=0.8;
c1=1.2;
c2=1.2;

% Initializations
iter=Max_iter;
vel=zeros(noP,dim);
pBestScore=zeros(noP);
pBest=zeros(noP,dim);
cg_curve=zeros(1,iter);

% Random initialization for agents.
pos=initialization(noP,dim,ub,lb); 

for i=1:noP
    pBestScore(i)=inf;
end

% Initialize gBestScore for a minimization problem
 gBestScore=inf;
 
    
for l=1:iter 
    
    % Return back the particles that go beyond the boundaries of the search
    % space
     for i=1:size(pos,1)
        Flag4ub=pos(i,:)>ub;
        Flag4lb=pos(i,:)<lb;
        pos(i,:)=(pos(i,:).*(~(Flag4ub+Flag4lb)))+ub.*Flag4ub+lb.*Flag4lb;
    end
    
    for i=1:size(pos,1)     
        %Calculate objective function for each particle
        fitness= fobj(pos(i,:)',da);
    
        if(pBestScore(i)>fitness)
            pBestScore(i)=fitness;
            pBest(i,:)=pos(i,:);
        end
        if(gBestScore>fitness)
            gBestScore=fitness;
            gBest=pos(i,:);
        end
    end

    %Update the W of PSO
    %Update the Velocity and Position of particles
    for i=1:size(pos,1)
        for j=1:size(pos,2)       
            vel(i,j)=w*vel(i,j)+c1*rand()*(pBest(i,j)-pos(i,j))+c2*rand()*(gBest(j)-pos(i,j));
            
            if(vel(i,j)>Vmax(1,j))
                vel(i,j)=Vmax(1,j);
            end
            if(vel(i,j)<-Vmax(1,j))
                vel(i,j)=-Vmax(1,j);
            end            
            pos(i,j)=pos(i,j)+vel(i,j);
        end
    end
     cg_curve(l)=gBestScore;
     disp(['PSO: 第', num2str(l), '迭代',  ', the best fitness is ', num2str(gBestScore)])
     disp(['第',num2str(l),'次寻优的最佳位置为：[',num2str(fix(gBest)),']'])
end
   
end