22 citations · 84 across the 31 of their papers we have counts for
36 papers
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…
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…
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…
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…