2 citations · 7 across the 11 of their papers we have counts for
4 papers · 1 filter
Faster Optimization Through Genetic Drift
Cella Florescu, Marc Kaufmann, Johannes Lengler +1
The compact Genetic Algorithm (cGA), parameterized by its hypothetical population size , offers a low-memory alternative to evolving a large offspring population of solutions. I…
Self-Adjusting Evolutionary Algorithms Are Slow on Multimodal Landscapes
Johannes Lengler, Konstantin Sturm
The one-fifth rule and its generalizations are a classical parameter control mechanism in discrete domains. They have also been transferred to control the offspring population size…
Plus Strategies are Exponentially Slower for Planted Optima of Random Height
Johannes Lengler, Leon Schiller, Oliver Sieberling
We compare the -EA and the -EA on the recently introduced benchmark DisOM, which is the OneMax function with randomly planted local optima. Previous work showed tha…
Hardest Monotone Functions for Evolutionary Algorithms
Marc Kaufmann, Maxime Larcher, Johannes Lengler +1
In this paper we revisit the question how hard it can be for the Evolutionary Algorithm to optimize monotone pseudo-Boolean functions. By introducing a more pessimistic sto…