Genetic Algorithm to find best parameter values of an estimaor
Having used genetic algorithms extensively in both professional projects and for my own entertainment, I think it is best to just code your own set of functions/classes for the specific project.  As you have seen, there are quite a few well-intended open-source GA packages out there. However, many of the fine details and tweaks necessary for a good GA are problem-specific.  It is also more convenient to work directly with your existing data structures, rather than adapt to someone else's worldview.  In other words, cost-benefit does not seem to work out when applying someone else's GA package.  You need a function for creating a random instance, a function for checking it is valid, a function for scoring it, and a mating function.  That's pretty much it!