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julia
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function [Y,Gb, FA]=POS_alg(FOB,Func, X_max, X_min, N, M, I_max, FA, V_max, V_min, c1, c2, W_max, W_min );
for i=1:M % Personal best initialize
x(i,:)=X_min+rand(1,N).*(X_max-X_min);
v(i,:)=V_min+rand(1,N).*(V_max-V_min);
Fit(i,:)=Func(x(i,:));
FA=FA+1;
end
Pb(i,:)=x(i,:); % solution
[bestFit,idx]=min(Fit);
Gb=x(idx,:); % The best solution corrente
for t=1:I_max
for i=1:M
% Update the velocity
% Calculate the weighting function
w=W_max-(W_max-W_min)*t/I_max;
v(i,:)=w*v(i,:)+c1*rand*(Pb(i,:)-x(i,:))+c2*rand*(Gb-x(i,:));
% Check the velocity
v(i,:)=bound(v(i,:),V_max,V_min);
% Update the position
x(i,:)=x(i,:)+v(i,:);
% Check the velocity
x(i,:)=bound(x(i,:),X_max,X_min);
Fit_i=Func(x(i,:));
FA=FA+1; % Increase the number of function evaluation counter
if Fit_i<Fit(i)
Fit(i)=Fit_i;
Pb(i,:)=x(i,:);
end
% Update the Gb
if bestFit>Fit(i)
Gb=Pb(i,:);
bestFit=Fit(i);
end
end
Y=Func(Gb);
algo='POS - The Best Fitness: %.15f';
graf_conver(Y,t,'b.',algo);
%fun_resp(Y,Gb,FOB) %Figure (not recommended )
end
end
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