混沌优化算法求极值matlab仿真代码

for k=1:100 for z=1:100 for a = 1: 3 X(a, 1) = rand(1); TempX(a) = 2 * X(a, 1); end if myjudge(TempX(1), TempX(2), TempX(3)) == 1 break end end for g = 1:3 MaxX(g) = TempX(g); end MaxF = myfunction(MaxX(1), MaxX(2), MaxX(3)); for i = 2:5000 for j =1:3 X(j, i) = 4 * X(j, i - 1) * (1 - X(j, i - 1)); TempX(j) = 2 * X(j, i); end if myjudge(TempX(1), TempX(2), TempX(3))==1 TempF = myFunction(TempX(1), TempX(2), TempX(3)); if TempF > MaxF MaxX(j) = TempX(j); MaxF = TempF; end end end %二次载波 for i = 1:3 X(i, 1) =rand(1); end for i = 2:5000 for j = 1:3 X(j, i) = 4 * X(j, i - 1) * (1 - X(j, i - 1)); end end for i = 1:5000 for j = 1:3 TempX(j) = MaxX(j) + 0.0001 * X(j, i); end if myjudge(TempX(1), TempX(2), TempX(3))==1 TempF = myfunction(TempX(1), TempX(2), TempX(3)); if TempF > MaxF MaxX(j) = TempX(j); MaxF = TempF; end end end MaxF = vpa(MaxF, 4); for i = 1:3 MaxX(i) = vpa(MaxX(i), 4); end Max(k)=MaxF; MaxX1(k)=MaxX(1); MaxX2(k)=MaxX(2); MaxX3(k)=MaxX(3); end subplot(2,2,1) plot(MaxX1(1,:)); subplot(2,2,2) plot(MaxX2(1,:)); subplot(2,2,3) plot(MaxX3(1,:)); subplot(2,2,4) plot(Max(1,:)); xlabel('k') ylabel('Max') grid on sz=subs(Max) [m,n]=max(sz); B=Max(n); B1=MaxX1(n); B2=MaxX2(n); B3=MaxX3(n);