Standard steady state genetic algorithms can hillclimb faster than mutation-only evolutionary algorithms

Corus, D. and Oliveto, P.S. (2018) Standard steady state genetic algorithms can hillclimb faster than mutation-only evolutionary algorithms. IEEE Transactions on Evolutionary Computation, 22 (5). pp. 720-732. ISSN 1089-778X

Abstract

Metadata

Authors/Creators:
  • Corus, D.
  • Oliveto, P.S.
Copyright, Publisher and Additional Information: © 2017 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Keywords: Neural and Evolutionary Computing
Dates:
  • Accepted: 5 August 2017
  • Published (online): 26 September 2017
  • Published: October 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
ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL (EPSRC)EP/M004252/1
Depositing User: Symplectic Sheffield
Date Deposited: 18 Aug 2017 11:40
Last Modified: 10 Nov 2023 16:10
Status: Published
Publisher: IEEE
Refereed: Yes
Identification Number: https://doi.org/10.1109/TEVC.2017.2745715
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