I started a little genetic algorithm project that I haven't gotten to work on too much yet, which could make for a cool tutorial. I've got a GA that solves the traveling salesman problem in the Go programming language. It actually solves it in N isolated populations, where you tell it to use N go routines. (Optimally I believe N would be 2x the number of cores your machine has).
Since Go is a systems language, I have it running as a http server that sends back the results to webpage that renders the JSON on a HTML5 Canvas.
What I really wanted to do is experiment with "migrating" solutions from one population to another, to see if I can get any speedup that way. Right now, the isolated populations sort of converge at the same speed, but some do better than others, because they converge to different local minima.
Since Go is a systems language, I have it running as a http server that sends back the results to webpage that renders the JSON on a HTML5 Canvas.
What I really wanted to do is experiment with "migrating" solutions from one population to another, to see if I can get any speedup that way. Right now, the isolated populations sort of converge at the same speed, but some do better than others, because they converge to different local minima.
Anyway, if you want to fork it, its here: https://github.com/YesSql/GolangTspGa