Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorWang, H-
dc.contributor.authorYang, S-
dc.contributor.authorIp, WH-
dc.contributor.authorWang, D-
dc.identifier.citationNatural Computing, 9(3): 703 - 725, Sep 2010en_US
dc.descriptionCopyright @ Springer Science + Business Media B.V. 2010.en_US
dc.description.abstractRecently, there has been an increasing concern from the evolutionary computation community on dynamic optimization problems since many real-world optimization problems are dynamic. This paper investigates a particle swarm optimization (PSO) based memetic algorithm that hybridizes PSO with a local search technique for dynamic optimization problems. Within the framework of the proposed algorithm, a local version of PSO with a ring-shape topology structure is used as the global search operator and a fuzzy cognition local search method is proposed as the local search technique. In addition, a self-organized random immigrants scheme is extended into our proposed algorithm in order to further enhance its exploration capacity for new peaks in the search space. Experimental study over the moving peaks benchmark problem shows that the proposed PSO-based memetic algorithm is robust and adaptable in dynamic environments.en_US
dc.description.sponsorshipThis work was supported by the National Nature Science Foundation of China (NSFC) under Grant No. 70431003 and Grant No. 70671020, the National Innovation Research Community Science Foundation of China under Grant No. 60521003, the National Support Plan of China under Grant No. 2006BAH02A09 and the Ministry of Education, science, and Technology in Korea through the Second-Phase of Brain Korea 21 Project in 2009, the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/01 and the Hong Kong Polytechnic University Research Grants under Grant G-YH60.en_US
dc.subjectParticle swarm optimizationen_US
dc.subjectMemetic algorithmen_US
dc.subjectDynamic optimization problemen_US
dc.subjectSelf-organized random immigrantsen_US
dc.subjectFuzzy cognition local searchen_US
dc.titleA particle swarm optimization based memetic algorithm for dynamic optimization problemsen_US
pubs.organisational-data/Brunel/Brunel (Active)-
pubs.organisational-data/Brunel/Brunel (Active)/School of Info. Systems, Comp & Maths-
pubs.organisational-data/Brunel/Research Centres (RG)-
pubs.organisational-data/Brunel/Research Centres (RG)/CIKM-
pubs.organisational-data/Brunel/School of Information Systems, Computing and Mathematics (RG)-
pubs.organisational-data/Brunel/School of Information Systems, Computing and Mathematics (RG)/CIKM-
Appears in Collections:Computer Science
Dept of Computer Science Research Papers

Files in This Item:
File Description SizeFormat 
Fulltext.pdf233.32 kBAdobe PDFView/Open

Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.