A new orthogonal array based crossover, with analysis of gene interactions, for evolutionary algorithms and its application to car door design

2.50
Hdl Handle:
http://hdl.handle.net/10547/250914
Title:
A new orthogonal array based crossover, with analysis of gene interactions, for evolutionary algorithms and its application to car door design
Authors:
Chan, K.Y.; Kwong, C.K.; Jiang, H.; Aydin, Mehmet Emin ( 0000-0002-4890-5648 ) ; Fogarty, T.C.
Abstract:
Recent research shows that orthogonal array based crossovers outperform standard and existing crossovers in evolutionary algorithms in solving parametrical problems with high dimensions and multi-optima. However, those crossovers employed so far, ignore the consideration of interactions between genes. In this paper, we propose a method to improve the existing orthogonal array based crossovers by integrating information of interactions between genes. It is empirically shown that the proposed orthogonal array based crossover outperforms significantly both the existing orthogonal array based crossovers and standard crossovers on solving parametrical benchmark functions that interactions exist between variables. To further compare the proposed orthogonal array based crossover with the existing crossovers in evolutionary algorithms, a validation test based on car door design is used in which the effectiveness of the proposed orthogonal array based crossover is studied.
Citation:
Chan, K.Y. et al (2010) 'A new orthogonal array based crossover, with analysis of gene interactions, for evolutionary algorithms and its application to car door design' Expert Systems with Applications 37 (5):3853-3862
Publisher:
Elsevier
Journal:
Expert Systems with Applications
Issue Date:
May-2010
URI:
http://hdl.handle.net/10547/250914
DOI:
10.1016/j.eswa.2009.11.033
Additional Links:
http://linkinghub.elsevier.com/retrieve/pii/S0957417409009750
Type:
Article
Language:
en
ISSN:
0957-4174
Appears in Collections:
Centre for Research in Distributed Technologies (CREDIT)

Full metadata record

DC FieldValue Language
dc.contributor.authorChan, K.Y.en_GB
dc.contributor.authorKwong, C.K.en_GB
dc.contributor.authorJiang, H.en_GB
dc.contributor.authorAydin, Mehmet Eminen_GB
dc.contributor.authorFogarty, T.C.en_GB
dc.date.accessioned2012-11-05T09:50:03Zen
dc.date.available2012-11-05T09:50:03Zen
dc.date.issued2010-05en
dc.identifier.citationChan, K.Y. et al (2010) 'A new orthogonal array based crossover, with analysis of gene interactions, for evolutionary algorithms and its application to car door design' Expert Systems with Applications 37 (5):3853-3862en_GB
dc.identifier.issn0957-4174en
dc.identifier.doi10.1016/j.eswa.2009.11.033en
dc.identifier.urihttp://hdl.handle.net/10547/250914en
dc.description.abstractRecent research shows that orthogonal array based crossovers outperform standard and existing crossovers in evolutionary algorithms in solving parametrical problems with high dimensions and multi-optima. However, those crossovers employed so far, ignore the consideration of interactions between genes. In this paper, we propose a method to improve the existing orthogonal array based crossovers by integrating information of interactions between genes. It is empirically shown that the proposed orthogonal array based crossover outperforms significantly both the existing orthogonal array based crossovers and standard crossovers on solving parametrical benchmark functions that interactions exist between variables. To further compare the proposed orthogonal array based crossover with the existing crossovers in evolutionary algorithms, a validation test based on car door design is used in which the effectiveness of the proposed orthogonal array based crossover is studied.en_GB
dc.language.isoenen
dc.publisherElsevieren_GB
dc.relation.urlhttp://linkinghub.elsevier.com/retrieve/pii/S0957417409009750en_GB
dc.titleA new orthogonal array based crossover, with analysis of gene interactions, for evolutionary algorithms and its application to car door designen
dc.typeArticleen
dc.identifier.journalExpert Systems with Applicationsen_GB
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