wmax=0.9;
wmin=0.4;
N = 40 ; %微粒数目
D=10;
a=-1;
b=1;
c1=2; %学习因子1
c2=2; %学习因子2
M=200 ; %最大迭代次数
xmax=100;xmin=-100;
vmax=100;vmin=-100;
format long;
for i=1:N
for j=1:D
x(i,j)=randn*2;
v(i,j)=randn*2;
end
fitness(i)=func1(x(i,:));
end
[bestfitness bestindex]=min(fitness);
tbest=x(bestindex,:);
gbest=x;
fitnessgbest=fitness;
fitnesstbest=bestfitness;
for i=1:M
% w=((M-i)/M)*(wmax-wmin)+wmin;
% w=(wmax-wmin)*tan(0.875*(1-(i/M)^0.5))+wmin;
w=(wmax-wmin)*atan(1.56*(1-(i/M)^0.4))+wmin;
for j=1:N
v(j,:)=w*v(j,:)+c1*rand*(gbest(j,:)-x(j,:))+c2*rand*(tbest-x(j,:));
v(j,find(v(j,:)>vmax))=vmax;
v(j,find(v(j,:)<vmin))=vmin;
x(j,:)=x(j,:)+v(j,:);
x(j,find(x(j,:)>xmax))=xmax;
x(j,find(x(j,:)<xmin))=xmin;
fitness(j)=func1(x(j,:));
end
for j=1:N
if fitness(j)<fitnessgbest(j)
gbest(j,:)=x(j,:);
fitnessgbest(j)=fitness(j);
end
if fitness(j)<fitnesstbest
tbest=x(j,:);
fitnesstbest=fitness(j);
end
end
yy(i)=fitnesstbest;
% yliw(i)=log10(fitnesstbest);
% ytan(i)=log10(fitnesstbest);
% yarc(i)=log10(fitnesstbest);
end
figure(2)
plot(yy,'--g')
hold on
plot(trace,'--r')
legend('PSO适应度值','DE适应度值')
ylabel('适应度')
xlabel('迭代的次数')
