The trouble with genetic algorithms is that they are hardly worth it. It's just one of metaheuristics [1], and despite being "biology-inspired" and good-soundin

The trouble with genetic algorithms is that they are hardly worth it. It's just one of metaheuristics [1], and despite being "biology-inspired" and good-sounding, it does perform worse than simpler alternatives like tabu search [2] or, even better, LAHC [3]. One of the reasons for that is that for local search the speed of neighborhood exploration is paramount, so theoretical advantages of GA get swamped by slower neighborhood iteration. In addition, LAHC or global annealing are way simpler to implement, they are literally just a few lines of code. [1]: https://en.wikipedia.org/wiki/Metaheuristic https://en.wikipedia.org/wiki/Metaheuristic [2]: https://en.wikipedia.org/wiki/Tabu_search https://en.wikipedia.org/wiki/Tabu_search [3]: https://link.springer.com/chapter/10.1007/978-3-642-41019-2_13 https://link.springer.com/chapter/10.1007/978-3-642-41019-2_...