activity
20242026
collaborators

13 papers

cs.NE2026

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…

cs.NE2026

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…

math.PR2026

A Tight Epidemic Threshold for Competing Stochastic Infection Processes with Mutually Exclusive Immunity

Nicolas Klodt, Martin S. Krejca

Stochastic infection processes are continuous-time Markov chains on graphs that assign each vertex one of multiple states, such as susceptible, infected, or recovered. Depending on…

math.PR2026

Reemergence of the Epidemic Threshold in SIRS Infections on Connected Stars

Andreas Göbel, Nicolas Klodt, Martin S. Krejca

The SIRS process is a continuous-time process for how infections spread on a graph. In this model, each vertex is in one of the following three states: susceptible (to the infectio…

cs.NE2026

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…

math.PR2025

Polymer Dynamics via Cliques: New Conditions for Approximations

Tobias Friedrich, Andreas Göbel, Martin S. Krejca +1

Abstract polymer models are systems of weighted objects, called polymers, equipped with an incompatibility relation. An important quantity associated with such models is the partit…