Using GA for optimization of expensive fitness function with constraints

Hi All,

I am using Genetic Algorithm for optimization of a computationally expensive fitness function which also has constraints . I am right now imposing constraints in the form of penalty in to the objective function since constraint violation can only be calculated at the end of the function evaluation. I wanted to use nonlcon rather to satisfy the constraints.

But my problem is that the fitness function evaluation is expensive and I cant afford to do it again for checking of constraint violation. I have seen some nested function formulations where using output function I can accumulate all the individual variable values for every generation.

As per what I was thinking, would it be possible to have sort of a matrix in which I can store all the individual values at the beginning of a generation update that matrix while my fitness evaluations and when I call nonlcon for constraint evaluation, then to look up that updated matrix for constraint violation. While I am trying to implement this, I have some doubts.

1) I remember reading in some forum that outputfcn for Genetic algo can be called either at the beginning of a generation or at the end. By default, it is at the end. I wont be able to execute my method if it calls at the end. Sadly I am not able to find how to call the outputfcn at the beginning rather than the end of a generation. Really need help on this!!!

2) Since my fitness function is computationally expensive, I am using Parallel evaluations. So Would it be possible to implement the above mentioned idea while using parallel option in matlab or it would create some difficulties??