Dang, D., Friedrich, T., Kötzing, T. et al. (5 more authors) (2016) Emergence of Diversity and its Benefits for Crossover in Genetic Algorithms. In: Parallel Problem Solving from Nature – PPSN XIV. Parallel Problem Solving from Nature (PPSN 2016), 17-21 Sep 2016, Edinburgh, UK. Lecture Notes in Computer Science, 9921 . Springer International Publishing
Abstract
Population diversity is essential for avoiding premature convergence in Genetic Algorithms (GAs) and for the effective use of crossover. Yet the dynamics of how diversity emerges in populations are not well understood. We use rigorous runtime analysis to gain insight into population dynamics and GA performance for a standard (µ+1) GA and the Jumpk test function. By studying the stochastic process underlying the size of the largest collection of identical genotypes we show that the interplay of crossover followed by mutation may serve as a catalyst leading to a sudden burst of diversity. This leads to improvements of the expected optimisation time of order Ω(n/ log n) compared to mutationonly algorithms like the (1+1) EA.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 Springer International Publishing AG. This is an author produced version of a paper subsequently published in Lecture Notes in Computer Science. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Genetic algorithms; crossover; diversity; runtime analysis; theory |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Funding Information: | Funder Grant number EUROPEAN COMMISSION - FP6/FP7 SAGE - 138086 ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL (EPSRC) EP/M004252/1 European Cooperation in Science and Technology CA15140 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 29 Jun 2016 10:24 |
Last Modified: | 19 Dec 2022 13:34 |
Published Version: | http://dx.doi.org/10.1007/978-3-319-45823-6_83 |
Status: | Published |
Publisher: | Springer International Publishing |
Series Name: | Lecture Notes in Computer Science |
Refereed: | Yes |
Identification Number: | 10.1007/978-3-319-45823-6_83 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:101311 |