Standard Steady State Genetic Algorithms Can Hillclimb Faster than Mutation-only Evolutionary Algorithms

Corus, D. and Oliveto, P.S. (2017) Standard Steady State Genetic Algorithms Can Hillclimb Faster than Mutation-only Evolutionary Algorithms. IEEE Transactions on Evolutionary Computation. ISSN 1089-778X

Abstract

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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:
  • Published (online): 26 September 2017
  • Accepted: 24 August 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: 07 Nov 2018 09:40
Published Version: https://doi.org/10.1109/TEVC.2017.2745715
Status: Published online
Publisher: IEEE
Refereed: Yes
Identification Number: https://doi.org/10.1109/TEVC.2017.2745715
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