collaborators

6 papers

cs.NE2026

The -EA in Dynamic Environments

Georg Hasebe, Johannes Lengler, Raghu Raman Ravi

We study the -EA in dynamic linear environments, where in every generation selection is performed with respect to a freshly sampled linear function with positive weights.…

cs.NE2026

Improved Runtime Bound for the EA on BinVal

Joris Belder, Johannes Lengler, Raghu Raman Ravi

We study the EA on the Binary Value function BinVal. We show that it needs at most function evaluations to find the optimum when $μ= o(n/\log…

cs.NE2026

Runtime Analysis of the -ES in a Homogenous Progress Model

Johannes Lengler, Raghu Raman Ravi

We introduce a new simple model to study the fitness progress of Evolution Strategies (ES) in generic problems. In this model, we bypass the underlying fitness landscape and assume…

cs.NE2025

Diversity-Preserving Exploitation of Crossover

Johannes Lengler, Tom Offermann

Crossover is a powerful mechanism for generating new solutions from a given population of solutions. Crossover comes with a discrepancy in itself: on the one hand, crossover usuall…

cs.NE2025

Achieving Tight Runtime Bounds on Jump by Proving that Genetic Algorithms Evolve Near-Maximal Population Diversity

Andre Opris, Johannes Lengler, Dirk Sudholt

The JUMP benchmark was the first problem for which crossover was proven to give a speed-up over mutation-only evolutionary algorithms. Jansen and Wegener (2002) proved an upper…

cs.NE2024

How Population Diversity Influences the Efficiency of Crossover

Sacha Cerf, Johannes Lengler

Our theoretical understanding of crossover is limited by our ability to analyze how population diversity evolves. In this study, we provide one of the first rigorous analyses of po…