Design and analysis of diversity-based parent selection schemes for speeding up evolutionary multi-objective optimisation

Covantes Osuna, E. orcid.org/0000-0001-5991-6927, Gao, W., Neumann, F. et al. (1 more author) (2018) Design and analysis of diversity-based parent selection schemes for speeding up evolutionary multi-objective optimisation. Theoretical Computer Science. ISSN 0304-3975

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2018 Elsevier B.V. This is an author produced version of a paper subsequently published in Theoretical Computer Science. 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: Parent selection; Evolutionary algorithms; Multi-objective optimisation; Diversity mechanisms; Runtime analysis; Theory
Dates:
  • Accepted: 4 June 2018
  • Published (online): 19 June 2018
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Funding Information:
FunderGrant number
EUROPEAN COMMISSION - FP6/FP7SAGE - 138086
Depositing User: Symplectic Sheffield
Date Deposited: 15 Jun 2018 14:56
Last Modified: 19 Jun 2019 00:41
Published Version: https://doi.org/10.1016/j.tcs.2018.06.009
Status: Published online
Publisher: Elsevier
Refereed: Yes
Identification Number: https://doi.org/10.1016/j.tcs.2018.06.009

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