using genetic algorithm optimizer to figure out points that satisfy the imposed constraints

I want to find points that satisfy a set of constraints only using GA. It is not necessary to be optimal points. Some of the constraints depend on simulation evaluations. I did it by providing a constant fitness function(e.g., f(x) = 1), but it gave me the following error: Failure in user-supplied fitness function evaluation. Cannot continue. Failure in initial user-supplied fitness function evaluation. GA cannot continue. any idea?

Answer 1

[Renee Coetsee]

There are couple reasons that you could be getting this error.

- This error occurs when the objective function produces a NaN output. To fix this, edit the function so that it does not produces NaN values, or set constraints on the function's inputs to prevent the objective function from producing NaN outputs.

- If you have nonlinear constraints, make sure that you are following this note in the documentation page for "ga":

"Note: Passing Extra Parameters (Optimization Toolbox) explains how to pass extra parameters to the objective function and nonlinear constraint functions, if necessary."

[Mustafa Al-tekreeti]

The objective function is a trivial function, f(x) = 1, and I am not passing any parameters.

Answer 2

[Alan Weiss]

You did not show us how you defined your objective function. Here is one that will work:

 fun = @(x)1;

Alan Weiss

MATLAB mathematical toolbox documentation

[Mustafa Al-tekreeti]

Hello Alan, for sure I did that