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Conference Paper: A Novel DE-ABC-Based Hybrid Algorithm for Global Optimization

TitleA Novel DE-ABC-Based Hybrid Algorithm for Global Optimization
Authors
Issue Date2012
PublisherSpringer. The Journal's web site is located at http://springerlink.com/content/105633/
Citation
The 7th International Conference on Intelligent Computing (ICIC), Zhengzhou, China, 11-14 August 2011. In Lecture Notes in Computer Science, 2012, v. 6840, p. 558-565 How to Cite?
AbstractA novel hybrid swarm intelligent algorithm DEABC, integrating differential evolution (DE) and artificial bee colony (ABC) algorithm, is proposed in this paper. By using global information obtained form DE population and bee colony, the exploration and exploitation abilities of DEABC algorithm are balanced. The DE population uses the global best to generate offspring every generation. The bee colony acquires the best individual after few generations. The experiments are performed on six benchmark functions to compare the efficiencies of DE, ABC, PSO and DEABC. The numerical results indicate the proposed algorithm outperforms other algorithms in terms of accuracy and convergence speed.
DescriptionLecture Notes in Computer Science vol. 6840 entitled: Bio-inspired computing and applications: 7th International Conference on Intelligent Computing, ICIC 2011, Zhengzhou, China, August 11-14 2011: revised selected papers
Persistent Identifierhttp://hdl.handle.net/10722/198947
ISBN
ISSN
2005 Impact Factor: 0.402
2015 SCImago Journal Rankings: 0.252

 

DC FieldValueLanguage
dc.contributor.authorLi, Len_US
dc.contributor.authorYao, FMen_US
dc.contributor.authorTan, LJen_US
dc.contributor.authorNiu, Ben_US
dc.contributor.authorXu, Jen_US
dc.date.accessioned2014-07-22T00:56:45Z-
dc.date.available2014-07-22T00:56:45Z-
dc.date.issued2012en_US
dc.identifier.citationThe 7th International Conference on Intelligent Computing (ICIC), Zhengzhou, China, 11-14 August 2011. In Lecture Notes in Computer Science, 2012, v. 6840, p. 558-565en_US
dc.identifier.isbn9783642245527-
dc.identifier.issn0302-9743-
dc.identifier.urihttp://hdl.handle.net/10722/198947-
dc.descriptionLecture Notes in Computer Science vol. 6840 entitled: Bio-inspired computing and applications: 7th International Conference on Intelligent Computing, ICIC 2011, Zhengzhou, China, August 11-14 2011: revised selected papers-
dc.description.abstractA novel hybrid swarm intelligent algorithm DEABC, integrating differential evolution (DE) and artificial bee colony (ABC) algorithm, is proposed in this paper. By using global information obtained form DE population and bee colony, the exploration and exploitation abilities of DEABC algorithm are balanced. The DE population uses the global best to generate offspring every generation. The bee colony acquires the best individual after few generations. The experiments are performed on six benchmark functions to compare the efficiencies of DE, ABC, PSO and DEABC. The numerical results indicate the proposed algorithm outperforms other algorithms in terms of accuracy and convergence speed.en_US
dc.languageengen_US
dc.publisherSpringer. The Journal's web site is located at http://springerlink.com/content/105633/en_US
dc.relation.ispartofLecture Notes in Computer Science-
dc.rightsThe original publication is available at www.springerlink.com-
dc.titleA Novel DE-ABC-Based Hybrid Algorithm for Global Optimizationen_US
dc.typeConference_Paperen_US
dc.identifier.emailXu, J: frankxu@hkucc.hku.hken_US
dc.identifier.doi10.1007/978-3-642-24553-4_74en_US
dc.identifier.scopuseid_2-s2.0-84862937127-
dc.identifier.hkuros231523en_US
dc.identifier.volume6840en_US
dc.identifier.spage558en_US
dc.identifier.epage565en_US
dc.publisher.placeHeidelberg; London-

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