The 1/5-th rule with rollbacks
Anton Bassin, Maxim Buzdalov · Proceedings of the Genetic and Evolutionary Computation Conference Companion · 2019
Self-adjustment of parameters can significantly improve the performance of evolutionary algorithms. A notable example is the (1 + (λ, λ)) genetic algorithm, where the adaptation of the population size helps to achieve the linear runtime on the OneMax problem. However, on problems which interact badly with the self-adjustment procedure, its usage can lead to performance degradation compared to static parameter choices. In particular, the one fifth rule is able to raise the population size too fast on problems which are too far away from the perfect fitness-distance correlation.