Self-adjusting population sizes for non-elitist evolutionary algorithms
Mario Alejandro Hevia Fajardo, Dirk Sudholt · Proceedings of the Genetic and Evolutionary Computation Conference · 2021
Recent theoretical studies have shown that self-adjusting mechanisms can provably outperform the best static parameters in evolutionary algorithms on discrete problems. However, the majority of these studies concerned elitist algorithms and we do not have a clear answer on whether the same mechanisms can be applied for non-elitist algorithms.