22 citations · 58 across the 19 of their papers we have counts for
18 papers · 1 filter
Runtime Analysis of a Compact Genetic Algorithm on a Truly Multi-valued OneMax Function
Martin S. Krejca, Carsten Witt
Recently, the runtime analysis of multi-valued estimation-of-distribution algorithms in the framework of Ben Jedidia et al. (TCS 2024) has made significant advancements. However, a…
Improved Runtime Guarantees for the SPEA2 Multi-Objective Optimizer
Benjamin Doerr, Martin S. Krejca, Milan Stanković
Together with the NSGA-II, the SPEA2 is one of the most widely used domination-based multi-objective evolutionary algorithms. For both algorithms, the known runtime guarantees are…
Speeding Up the NSGA-II via Dynamic Population Sizes
Benjamin Doerr, Martin S. Krejca, Simon Wietheger
Multi-objective evolutionary algorithms (MOEAs) are among the most widely and successfully applied optimizers for multi-objective problems. However, to store many optimal trade-off…
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…
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…
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…