When move acceptance selection hyper-heuristics outperform metropolis and elitist evolutionary algorithms and when not

Lissovoi, A., Oliveto, P.S. and Warwicker, J.A. (2023) When move acceptance selection hyper-heuristics outperform metropolis and elitist evolutionary algorithms and when not. Artificial Intelligence, 314. 103804. ISSN 0004-3702

Abstract

Metadata

Item Type: Article
Authors/Creators:
  • Lissovoi, A.
  • Oliveto, P.S.
  • Warwicker, J.A.
Copyright, Publisher and Additional Information:

© 2022 Elsevier B.V. This is an author produced version of a paper subsequently published in Artificial Intelligence. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/).

Keywords: Hyper-heuristics; Runtime analysis; Non-elitism; Metropolis; Move acceptance operators; Theory
Dates:
  • Published: January 2023
  • Published (online): 4 October 2022
  • Accepted: 3 October 2022
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Funding Information:
Funder
Grant number
ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL
EP/M004252/1
ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL
UNSPECIFIED
Depositing User: Symplectic Sheffield
Date Deposited: 18 Oct 2022 16:18
Last Modified: 25 Sep 2024 14:00
Status: Published
Publisher: Elsevier BV
Refereed: Yes
Identification Number: 10.1016/j.artint.2022.103804
Open Archives Initiative ID (OAI ID):

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Filename: Manuscript.pdf

Licence: CC-BY-NC-ND 4.0

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