Analysing the robustness of evolutionary algorithms to noise : refined runtime bounds and an example where noise is beneficial

Sudholt, D. orcid.org/0000-0001-6020-1646 (2020) Analysing the robustness of evolutionary algorithms to noise : refined runtime bounds and an example where noise is beneficial. Algorithmica. ISSN 0178-4617

Metadata

Authors/Creators:
Copyright, Publisher and Additional Information: © 2020 The Author. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made (http://creativecommons.org/licenses/by/4.0/).
Keywords: Evolutionary algorithms; Noisy optimisation; Robustness; Runtime analysis; Theory; Uncertainty
Dates:
  • Accepted: 7 January 2020
  • Published (online): 25 January 2020
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 06 Mar 2020 14:28
Last Modified: 06 Mar 2020 14:28
Status: Published online
Publisher: Springer Nature
Refereed: Yes
Identification Number: https://doi.org/10.1007/s00453-020-00671-0

Share / Export

Statistics