55 citations · 290 across the 25 of their papers we have counts for
26 papers
First Steps Towards a Runtime Analysis of Neuroevolution
Paul Fischer, Emil Lundt Larsen, Carsten Witt
We consider a simple setting in neuroevolution where an evolutionary algorithm optimizes the weights and activation functions of a simple artificial neural network. We then define…
Fast Pareto Optimization Using Sliding Window Selection
Frank Neumann, Carsten Witt
Pareto optimization using evolutionary multi-objective algorithms has been widely applied to solve constrained submodular optimization problems. A crucial factor determining the ru…
3-Objective Pareto Optimization for Problems with Chance Constraints
Frank Neumann, Carsten Witt
Evolutionary multi-objective algorithms have successfully been used in the context of Pareto optimization where a given constraint is relaxed into an additional objective. In this…
Runtime Analysis of the (1+1) EA on Weighted Sums of Transformed Linear Functions
Frank Neumann, Carsten Witt
Linear functions play a key role in the runtime analysis of evolutionary algorithms and studies have provided a wide range of new insights and techniques for analyzing evolutionary…
The Compact Genetic Algorithm Struggles on Cliff Functions
Frank Neumann, Dirk Sudholt, Carsten Witt
The compact genetic algorithm (cGA) is an non-elitist estimation of distribution algorithm which has shown to be able to deal with difficult multimodal fitness landscapes that are…
Runtime Analysis of Single- and Multi-Objective Evolutionary Algorithms for Chance Constrained Optimization Problems with Normally Distributed Random Variables
Frank Neumann, Carsten Witt
Chance constrained optimization problems allow to model problems where constraints involving stochastic components should only be violated with a small probability. Evolutionary al…