Memetic Algorithms Beat Evolutionary Algorithms on the Class of Hurdle Problems

Nguyen, P.T.H. and Sudholt, D. orcid.org/0000-0001-6020-1646 (2018) Memetic Algorithms Beat Evolutionary Algorithms on the Class of Hurdle Problems. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2018). Genetic and Evolutionary Computation Conference (GECCO 2018), 15-19 Jul 2018, Kyoto, Japan. ACM . ISBN 978-1-4503-5618-3

Abstract

Metadata

Authors/Creators:
Copyright, Publisher and Additional Information: © 2018 Copyright held by the owner/author(s). Publication rights licensed to the Association for Computing Machinery. This is an author-produced version of a paper accepted for publication. Uploaded in accordance with the publisher's self-archiving policy.
Keywords: Evolutionary algorithms; hybridisation; iterated local search; local search; memetic algorithms; running time analysis; theory
Dates:
  • Published: 2 July 2018
  • Accepted: 24 March 2018
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: 16 May 2018 13:26
Last Modified: 20 Aug 2018 11:44
Published Version: https://dx.doi.org/10.1145/3205455.3205456
Status: Published online
Publisher: ACM
Refereed: Yes
Identification Number: https://doi.org/10.1145/3205455.3205456

Share / Export

Statistics