Archivers for Single- and Multi-objective Evolutionary Optimization Algorithms

In this article, we briefly summarize some of the main results of the book "Archiving Strategies for Evolutionary Multi-objective Optimization Algorithms" by 0. Schiitze and C. Hernindez, Springer, 2021. In this book, several archiving strategies are proposed and analyzed that yield certain approximation qualities ofthe solution sets (mainly the Pareto front and the set of approximate solutions) in the limit, where these approximation qualities can be determined a priori. Further, the benefits of the use of these strategies as external archives to given evolutionary algorithms are demonstrated.