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Conference Paper: Parameter control by the entire search history: Case study of history-driven evolutionary algorithm

TitleParameter control by the entire search history: Case study of history-driven evolutionary algorithm
Authors
Issue Date2010
PublisherInstitute of Electrical and Electronics Engineers. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=4235
Citation
The 6th IEEE World Congress on Computational Intelligence cum IEEE Congress on Evolutionary Computation (WCCI-CEC 2010), Barcelona, Spain, 18-23 July 2010. In IEEE Transactions on Evolutionary Computation, 2010, p. 1-8 How to Cite?
AbstractHistory-driven Evolutionary Algorithm (HdEA) is an EA that uses the entire search history to improve searching performance. By building the approximated fitness landscape and estimating the gradient using the entire history, HdEA performs a parameter-less adaptive mutation. In order to decrease the number of parameters that makes the HdEA more robust, this paper proposes a novel adaptive parameter control system. This system is as an add-on component to HdEA, which uses the whole search history in HdEA to control the parameters in an automatic manner. The performance of the proposed system is examined on 34 benchmark functions. The results shows that the parameter control system gives similar or better performance in 24 functions and has the benefit that two parameters of the HdEA are eliminated; they are set and varied automatically by the system. © 2010 IEEE.
DescriptionSpecial Session on Evolutionary Computer Vision
Persistent Identifierhttp://hdl.handle.net/10722/196719
ISBN
ISSN
2015 Impact Factor: 5.908
2015 SCImago Journal Rankings: 4.308

 

DC FieldValueLanguage
dc.contributor.authorLeung, SW-
dc.contributor.authorYuen, SY-
dc.contributor.authorChow, CK-
dc.date.accessioned2014-04-24T02:10:36Z-
dc.date.available2014-04-24T02:10:36Z-
dc.date.issued2010-
dc.identifier.citationThe 6th IEEE World Congress on Computational Intelligence cum IEEE Congress on Evolutionary Computation (WCCI-CEC 2010), Barcelona, Spain, 18-23 July 2010. In IEEE Transactions on Evolutionary Computation, 2010, p. 1-8-
dc.identifier.isbn978-1-4244-6909-3-
dc.identifier.issn1089-778X-
dc.identifier.urihttp://hdl.handle.net/10722/196719-
dc.descriptionSpecial Session on Evolutionary Computer Vision-
dc.description.abstractHistory-driven Evolutionary Algorithm (HdEA) is an EA that uses the entire search history to improve searching performance. By building the approximated fitness landscape and estimating the gradient using the entire history, HdEA performs a parameter-less adaptive mutation. In order to decrease the number of parameters that makes the HdEA more robust, this paper proposes a novel adaptive parameter control system. This system is as an add-on component to HdEA, which uses the whole search history in HdEA to control the parameters in an automatic manner. The performance of the proposed system is examined on 34 benchmark functions. The results shows that the parameter control system gives similar or better performance in 24 functions and has the benefit that two parameters of the HdEA are eliminated; they are set and varied automatically by the system. © 2010 IEEE.-
dc.languageeng-
dc.publisherInstitute of Electrical and Electronics Engineers. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=4235-
dc.relation.ispartofIEEE Transactions on Evolutionary Computation-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rightsIEEE Transactions on Evolutionary Computation. Copyright © Institute of Electrical and Electronics Engineers.-
dc.titleParameter control by the entire search history: Case study of history-driven evolutionary algorithm-
dc.typeConference_Paper-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/CEC.2010.5585945-
dc.identifier.scopuseid_2-s2.0-79959444283-
dc.identifier.spage1-
dc.identifier.epage8-
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 160603 amended-

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