Multi variable Simulated Annealing with different bounds

Question

Spyros Polychronopoulos 2018-9-12

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/418749-multi-variable-simulated-annealing-with-different-bounds

编辑： Spyros Polychronopoulos 2018-9-21

采纳的回答： Alan Weiss

在 MATLAB Online 中打开

Hi there, I have this function that has two variables x and y

fun = @(x,y) x+y-5;

I would like to find the global minimum of this function using SA optimiser. Now the problem that I have here is that I want to use different boundary conditions for x and y like so

x0 = rand;
LBx = 0; % LBx - lower bound for x
UBx= 10; % UBx - upper bound for x
y0 = rand;
LBy = -2; % LB - lower bound for x
UBy= 3; % UB - upper bound for y

The line below is obviously not working but I am posting it as a reference to explain what I am trying to do

[x,y,fval]=simulannealbnd(fun,x0,LBx,UBx,y0,LBy,UBy); %simulated annealing

Thank you very much in advance for your help

0 个评论
显示 -2更早的评论隐藏 -2更早的评论

请先登录，再进行评论。

请先登录，再回答此问题。

Answer 1

Alan Weiss 2018-9-13

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/418749-multi-variable-simulated-annealing-with-different-bounds#answer_336637

Global Optimization Toolbox solvers, like Optimization Toolbox™ solvers, require you to put all your variables into one vector. The same with the bounds. See Compute Objective Functions and Bound Constraints.

Alan Weiss

MATLAB mathematical toolbox documentation