x = 1:0.01:2;

y = sin(10*pi*x) ./ x;

figure

plot(x, y)

title('绘制目标函数曲线图—Jason niu');

hold on

c1 = 1.49445;

c2 = 1.49445;

maxgen = 50;

sizepop = 10;   

Vmax = 0.5;

Vmin = -0.5;

popmax = 2;

popmin = 1;

ws = 0.9;

we = 0.4;

for i = 1:sizepop

    pop(i,:) = (rands(1) + 1) / 2 + 1;

    V(i,:) = 0.5 * rands(1);  

    fitness(i) = fun(pop(i,:));

end

[bestfitness bestindex] = max(fitness);

zbest = pop(bestindex,:);

gbest = pop;

fitnessgbest = fitness;

fitnesszbest = bestfitness;   

for i = 1:maxgen

    w = ws - (ws-we)*(i/maxgen);

    for j = 1:sizepop

        V(j,:) = w*V(j,:) + c1*rand*(gbest(j,:) - pop(j,:)) + c2*rand*(zbest - pop(j,:));

        V(j,find(V(j,:)>Vmax)) = Vmax;

        V(j,find(V(j,:)<Vmin)) = Vmin;

        pop(j,:) = pop(j,:) + V(j,:);

        pop(j,find(pop(j,:)>popmax)) = popmax;

        pop(j,find(pop(j,:)<popmin)) = popmin;

        fitness(j) = fun(pop(j,:));

    end

    for j = 1:sizepop

        if fitness(j) > fitnessgbest(j)

            gbest(j,:) = pop(j,:);

            fitnessgbest(j) = fitness(j);

        end

        if fitness(j) > fitnesszbest

            zbest = pop(j,:);

            fitnesszbest = fitness(j);

        end

    end

    yy(i) = fitnesszbest;

end

[fitnesszbest zbest]

plot(zbest, fitnesszbest,'r*')

figure

plot(yy)

title('PSO：PSO算法(快于GA算法)+ω参数实现找到最优个体适应度—Jason niu','fontsize',12);

xlabel('进化代数','fontsize',12);ylabel('适应度','fontsize',12);