matlab实现混沌粒子群算法

可以使用以下代码实现混沌粒子群算法：

function [gbest,gbestval]=cpsopso(fhd,n,lb,ub,dim,max_iter)
% fhd: function handle
% n: population size
% lb: lower bound of variables
% ub: upper bound of variables
% dim: dimension of variables
% max_iter: maximum number of iterations

% initialize the population
pop=lb+(ub-lb).*rand(n,dim);
vel=zeros(n,dim);
pbest=pop;
pbestval=feval(fhd,pbest);
[gbestval,idx]=min(pbestval);
gbest=pbest(idx,:);

% set the parameters
c1=2;
c2=2;
w=0.9;
w_damp=0.99;
max_vel=0.2*(ub-lb);
min_vel=-max_vel;

% main loop
for iter=1:max_iter
% update the velocity and position
vel=w*vel+c1*rand(n,dim).*(pbest-pop)+c2*rand(n,dim).*(repmat(gbest,n,1)-pop);
vel(vel>max_vel)=max_vel(vel>max_vel);
vel(vel<min_vel)=min_vel(vel<min_vel);
pop=pop+vel;
pop(pop>ub)=ub(pop>ub);
pop(pop<lb)=lb(pop<lb);

% evaluate the fitness
fit=feval(fhd,pop);

% update the personal best
idx=fit<pbestval;
pbest(idx,:)=pop(idx,:);
pbestval(idx)=fit(idx);

% update the global best
[min_fit,idx]=min(pbestval);
if min_fit<gbestval
gbest=pbest(idx,:);
gbestval=min_fit;
end

% update the inertia weight
w=w*w_damp;
end

end

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