fmincon is giving better results than ga for a nonlinear constrained optimization problem.

Question

Nayan Rawat 2019-7-12

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/471445-fmincon-is-giving-better-results-than-ga-for-a-nonlinear-constrained-optimization-problem

编辑： Matt J 2019-7-12

I used fmincon and ga for the same nonlinear constrained optimization (7-300 variables) but fmincon is giving much better results (all ceq<10^-8) while ga is not able to satisfy equality constraints. Help please.

Also: fmincon results vary with initial guess, step tolerance and constraint tolerance. What step tolerance and constraint tolerance should i choose?

2 个评论
显示无隐藏无

Matt J 2019-7-12

What help is required? If fmincon responds better to the problem, why not just use that instead?

Nayan Rawat 2019-7-12

Because fmincon result depends on initial guess. Changing the initial guess is changing the result while the ceq constraints are still very small(1e-8). This means that it may be a local minimum. I want to use other algorithms which give global minimum too (like ga, patternsearch etc).

请先登录，再进行评论。

请先登录，再回答此问题。

Answer 1

Star Strider 2019-7-12

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/471445-fmincon-is-giving-better-results-than-ga-for-a-nonlinear-constrained-optimization-problem#answer_382967

在 MATLAB Online 中打开

The ga function produces its best results if you override the default population matrix with one of your own. I always use an options structure similar to:

PopSz = 500;
Parms = 6;
opts = optimoptions('ga', 'PopulationSize',PopSz, 'InitialPopulationMatrix',randi(1E+4,PopSz,Parms)*1E-3, 'MaxGenerations',2E3, 'PlotFcn',@gaplotbestf, 'PlotInterval',1);

where ‘PopSz’ is the size (dimension 1) of the population matrix, and ‘Parms’ (dimension 2) is the number of parameters to optimise. It takes a bit longer, however it almost always converges successfully, if a solution exists. I use randi to more efficiently control the range of the random matrix.