Illustrating the Efficiency of Popular Evolutionary Multi-Objective Algorithms Using Runtime Analysis
Duc-Cuong Dang, Andre Opris, Dirk Sudholt · Proceedings of the Genetic and Evolutionary Computation Conference · 2024
Runtime analysis has recently been applied to popular evolutionary multi-objective (EMO) algorithms like NSGA-II in order to establish a rigorous theoretical foundation. However, most analyses showed that these algorithms have the same performance guarantee as the simple (G)SEMO algorithm. To our knowledge, there are no runtime analyses showing an advantage of a popular EMO algorithm over the simple algorithm for deterministic problems.