Generalized jump functions
Henry Bambury, Antoine Bultel, Benjamin Doerr · Proceedings of the Genetic and Evolutionary Computation Conference · 2021
Jump functions are the most studied non-unimodal benchmark in the theory of evolutionary algorithms (EAs). They have significantly improved our understanding of how EAs escape from local optima. However, their particular structure - to leave the local optimum the EA can only jump directly to the global optimum - raises the question of how representative the recent findings are.