Objective and Nonlinear Constraints in the Same Function for genetic algorithm

Hi, I have a question about how to reduce computational time of GA with non-linear constraints and mixed-integer variables.

I have referered to the page "Objective and Nonlinear Constraints in the Same Function" and seems that this is exactly what I want to solve.

https://jp.mathworks.com/help/optim/ug/objective-and-nonlinear-constraints-in-the-same-function.html?lang=en#d117e7977

However, in this page, it is stated that Because of the way ga calls nonlinear constraint functions, the technique in this example usually does not reduce the number of calls to the objective or constraint functions.

Actually, I tried the solution to my codes and it did not work.

Since there is almost the same question (below) but without answer, it would be appreciated if you could give me advice.

(Reletated question)

Share information between objective and constraint function with genetic algorithm

https://jp.mathworks.com/matlabcentral/answers/443733-share-information-between-objective-and-constraint-function-with-genetic-algorithm

[Gifari Zulkarnaen]

As noted there, I don't think we can do this in ga (or other global optimization toolbox's solvers). Unless we edit the native code of the toolbox. I am interested in this, because I also often face problem with expensive function. By default, ga uses ALGA for handling nonlinearly constrained problem. I am thinking to edit the native code so that every time it calls objective or nonlinear function, it returns three value: objective value, linear constraint, nonlinear constraint, so that we can use one same function for objective and nonlinear constraint. But currently I don't have time for this, maybe in the future.

[Yohei]

Dear Gifari,

Thank you so much for insightfulll comment. I understood that reducing the computational time with current toolbox function is difficult. I am very happy if you could share the edited native code in the future.