How to optimize a Objective function which depends on Random variable (Noise) subjected to multiple constraints using Genetic Algorithm? But Constraints are independent of Random variable.

Hi,I am solving a optimization problem using Genetic Algorithm.My objective function depends on Random variable.But my N constraints are independent of that random variable. How can Code this using Matlab.

[Alan Weiss]

Sorry, I do not understand what you are asking. Does your objective function value change every time you evaluate it at the same point? If so, this violates the assumptions of the genetic algorithm solver ga, and so you should not use ga. However, if the noise is deterministic in the sense that repeated evaluations of the objective function at the same point give the same result, then as far as ga is concerned you have a non-random function to optimize, and there is no issue.

Alan Weiss

MATLAB mathematical toolbox documentation

[Matt J]

My objective function depends on Random variable.

I think what you really mean is that the objective function depends on one particular realization of a random variable, as for example in a maximum likelihood estimation problem. In this case, your objective function is not really stochastic, and there is no issue.

[Walter Roberson]

I suspect this was duplicated by https://www.mathworks.com/matlabcentral/answers/379925-how-can-i-optimize-the-following-conditions-using-genetic-algorithms