More effective randomized search heuristics for graph coloring through dynamic optimization

Bossek, J., Neumann, F., Peng, P. et al. (1 more author) (2020) More effective randomized search heuristics for graph coloring through dynamic optimization. In: GECCO 2020: Proceedings of the Genetic and Evolutionary Computation Conference. GECCO 2020 : Genetic and Evolutionary Computation Conference, 08-12 Jul 2020, Cancún, Mexico. ACM Digital Library , pp. 1277-1285. ISBN 9781450371285

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Copyright, Publisher and Additional Information: © 2020 Copyright held by the owner/author(s). Publication rights licensed to ACM. This is an author-produced version of a paper subsequently published in GECCO '20: Proceedings of the 2020 Genetic and Evolutionary Computation Conference. Uploaded in accordance with the publisher's self-archiving policy.
Keywords: Evolutionary algorithms; dynamic optimization; running time analysis; theory
Dates:
  • Accepted: 20 March 2020
  • Published (online): June 2020
  • Published: June 2020
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: 27 Apr 2020 10:47
Last Modified: 15 Oct 2020 11:37
Status: Published
Publisher: ACM Digital Library
Refereed: Yes
Identification Number: https://doi.org/10.1145/3377930.3390174
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