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cs.NE2025

Proven Approximation Guarantees in Multi-Objective Optimization: SPEA2 Beats NSGA-II

Yasser Alghouass, Benjamin Doerr, Martin S. Krejca +1

Together with the NSGA-II and SMS-EMOA, the strength Pareto evolutionary algorithm 2 (SPEA2) is one of the most prominent dominance-based multi-objective evolutionary algorithms (M…

cs.NE2025

Near-Tight Runtime Guarantees for Many-Objective Evolutionary Algorithms

Simon Wietheger, Benjamin Doerr

Despite significant progress in the field of mathematical runtime analysis of multi-objective evolutionary algorithms (MOEAs), the performance of MOEAs on discrete many-objective p…

cs.NE2025

Evolutionary Algorithms Are Significantly More Robust to Noise When They Ignore It

Denis Antipov, Benjamin Doerr

Randomized search heuristics (RSHs) are known to have a certain robustness to noise. Mathematical analyses trying to quantify rigorously how robust RSHs are to a noisy access to th…

cs.NE2025

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…

cs.NE2025

Runtime Analysis of the Compact Genetic Algorithm on the LeadingOnes Benchmark

Marcel Chwiałkowski, Benjamin Doerr, Martin S. Krejca

The compact genetic algorithm (cGA) is one of the simplest estimation-of-distribution algorithms (EDAs). Next to the univariate marginal distribution algorithm (UMDA) -- another si…