5 papers · 1 filter
Towards a Rigorous Understanding of the Population Dynamics of the NSGA-III: Tight Runtime Bounds
Andre Opris
Evolutionary algorithms are widely used for solving multi-objective optimization problems. A prominent example is NSGA-III, which is particularly well suited for solving problems i…
Many Objective Problems Where Crossover is Provably Essential
Andre Opris
This article addresses theory in evolutionary many-objective optimization and focuses on the role of crossover operators. The advantages of using crossover are hardly understood an…
A First Runtime Analysis of the PAES-25: An Enhanced Variant of the Pareto Archived Evolution Strategy
Andre Opris
This paper presents a first mathematical runtime analysis of PAES-25, an enhanced version of the original Pareto Archived Evolution Strategy (PAES) coming from the study of telecom…
Tight Runtime Guarantees From Understanding the Population Dynamics of the GSEMO Multi-Objective Evolutionary Algorithm
Benjamin Doerr, Martin Krejca, Andre Opris
The global simple evolutionary multi-objective optimizer (GSEMO) is a simple, yet often effective multi-objective evolutionary algorithm (MOEA). By only maintaining non-dominated s…
Achieving Tight Runtime Bounds on Jump by Proving that Genetic Algorithms Evolve Near-Maximal Population Diversity
Andre Opris, Johannes Lengler, Dirk Sudholt
The JUMP benchmark was the first problem for which crossover was proven to give a speed-up over mutation-only evolutionary algorithms. Jansen and Wegener (2002) proved an upper…