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Multi-Level Neutrality in Optimization

Johnson, Colin G. (2008) Multi-Level Neutrality in Optimization. In: 2008 IEEE Congress on Evolutionary Computation. IEEE, pp. 2604-2609. ISBN 978-1-4244-1822-0. (doi:10.1109/CEC.2008.4631147) (KAR id:24007)

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Official URL
http://dx.doi.org/10.1109/CEC.2008.4631147

Abstract

This paper explores the idea of neutrality in heuristic optimization algorithms. In particular, the effect of having multiple levels of neutrality in representations is explored. Two experiments using a fitness-adaptive walk algorithm are carried out: the first is concerned with function optimization with Random Boolean Networks, the second with a tunable neutral mapping applied to the hierarchical if-and-only-if function. In both of these cases it is shown that a two-level neutral mapping can be found that performs better than both nonneutral mappings and mappings with a single level of neutrality.

Item Type: Book section
DOI/Identification number: 10.1109/CEC.2008.4631147
Uncontrolled keywords: Genetic Algorithms; Neutrality; Hill-Climbing; Optimization
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Mark Wheadon
Date Deposited: 29 Mar 2010 12:10 UTC
Last Modified: 16 Feb 2021 12:34 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/24007 (The current URI for this page, for reference purposes)
Johnson, Colin G.: https://orcid.org/0000-0002-9236-6581
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