One GA technique that has not been applied to GEPs yet, as far as I am aware, is the idea of a structure population. In GA literature these are call cGA or cellular genetic algorithms. The idea is very nice and seems natural, appears to perform well, and has some good work done in studying the effects of different topologies. One of my professors is even doing something with a structure that is very cool, and I may post about when he publishes his paper on it.
The most obvious thing to do would be to just check if cGEPs are better performing then GEPs, but it would also be interesting to find some interesting shape or strategy to contribute to the research, as well as extend it to GEP at the same time.
There are so many cool things to do with GEPs! A young method and a small community has its advantages sometimes.
It would be great if you could put some code snippets in with your posts to make these techniques clearer for people who aren't familiar with them!
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