6 citations · 11 across the 9 of their papers we have counts for
18 papers · 1 filter
Comma Selection Outperforms Plus Selection on OneMax with Randomly Planted Optima
Joost Jorritsma, Johannes Lengler, Dirk Sudholt
It is an ongoing debate whether and how comma selection in evolutionary algorithms helps to escape local optima. We propose a new benchmark function to investigate the benefits of…
Analysing Equilibrium States for Population Diversity
Johannes Lengler, Andre Opris, Dirk Sudholt
Population diversity is crucial in evolutionary algorithms as it helps with global exploration and facilitates the use of crossover. Despite many runtime analyses showing advantage…
Tight Runtime Bounds for Static Unary Unbiased Evolutionary Algorithms on Linear Functions
Carola Doerr, Duri Andrea Janett, Johannes Lengler
In a seminal paper in 2013, Witt showed that the (1+1) Evolutionary Algorithm with standard bit mutation needs time to find the optimum of any linear function…
Population Diversity Leads to Short Running Times of Lexicase Selection
Thomas Helmuth, Johannes Lengler, William La Cava
In this paper we investigate why the running time of lexicase parent selection is empirically much lower than its worst-case bound of O(N*C). We define a measure of population dive…
OneMax is not the Easiest Function for Fitness Improvements
Marc Kaufmann, Maxime Larcher, Johannes Lengler +1
We study the success rule for controlling the population size of the -EA. It was shown by Hevia Fajardo and Sudholt that this parameter control mechanism can run i…
Self-adjusting Population Sizes for the -EA on Monotone Functions
Marc Kaufmann, Maxime Larcher, Johannes Lengler +1
We study the -EA with mutation rate for , where the population size is adaptively controlled with the -success rule. Recently, Hevia Fajardo and Sudho…