Analysis of the (1+1) EA on LeadingOnes with Constraints
Neural and Evolutionary Computing
2023-05-30 v1
Abstract
Understanding how evolutionary algorithms perform on constrained problems has gained increasing attention in recent years. In this paper, we study how evolutionary algorithms optimize constrained versions of the classical LeadingOnes problem. We first provide a run time analysis for the classical (1+1) EA on the LeadingOnes problem with a deterministic cardinality constraint, giving as the tight bound. Our results show that the behaviour of the algorithm is highly dependent on the constraint bound of the uniform constraint. Afterwards, we consider the problem in the context of stochastic constraints and provide insights using experimental studies on how the (+1) EA is able to deal with these constraints in a sampling-based setting.
Keywords
Cite
@article{arxiv.2305.18267,
title = {Analysis of the (1+1) EA on LeadingOnes with Constraints},
author = {Tobias Friedrich and Timo Kötzing and Aneta Neumann and Frank Neumann and Aishwarya Radhakrishnan},
journal= {arXiv preprint arXiv:2305.18267},
year = {2023}
}