基于惯性权重和学习因子动态调整的粒子群算法.zip

function y=fun(x,index) % x代表参数，index代表测试的函数的选择 % 该测试函数为通用测试函数，可以移植 % 目录 % 函数名 位置 最优值 % 1.Sphere 0 0 % 2.Camel 多个 % 3.Rosenbrock switch index case 1 %Sphere函数 y=sum(x.^2); case 2 % xx=x(1);yy=x(2);y=20.*exp(-0.2.*sqrt((xx.^2+yy.^2)/2))+exp((cos(2.*pi.*xx)+cos(2.*pi.*yy))/2)-exp(1)-20; case 3 %Rosenbrock函数 y=0; for i=2:length(x) y=y+100*(x(i)-x(i-1)^2)^2+(x(i-1)-1)^2; end case 4 %Ackley函数 a = 20; b = 0.2; c = 2*pi; s1 = 0; s2 = 0; for i=1:length(x) s1 = s1+x(i)^2; s2 = s2+cos(c*x(i)); end y = -a*exp(-b*sqrt(1/length(x)*s1))-exp(1/length(x)*s2)+a+exp(1); case 5 %Rastrigin函数 s = 0; for j = 1:length(x) s = s+(x(j)^2-10*cos(2*pi*x(j))); end y = 10*length(x)+s; case 6 %Griewank函数 fr = 4000; s = 0; p = 1; for j = 1:length(x); s = s+x(j)^2; end for j = 1:length(x); p = p*cos(x(j)/sqrt(j)); end y = s/fr-p+1; case 7 %Shubert函数 s1 = 0; s2 = 0; for i = 1:5 s1 = s1+i*cos((i+1)*x(1)+i); s2 = s2+i*cos((i+1)*x(2)+i); end y = s1*s2; case 8 %beale函数 y = (1.5-x(1)*(1-x(2)))^2+(2.25-x(1)*(1-x(2)^2))^2+(2.625-x(1)*(1-x(2)^3))^2; case 9 %Schwefel函数 s = sum(-x.*sin(sqrt(abs(x)))); y = 418.9829*length(x)+s; case 10 %Schaffer函数 temp=x(1)^2+x(2)^2; y=0.5-(sin(sqrt(temp))^2-0.5)/(1+0.001*temp)^2; otherwise disp('no such function, please choose another'); endfunction [outputArg1,outputArg2] = untitled2(inputArg1,inputArg2) %UNTITLED2 此处显示有关此函数的摘要 % 此处显示详细说明 outputArg1 = inputArg1; outputArg2 = inputArg2; end