Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorYan, Y-
dc.contributor.authorWang, H-
dc.contributor.authorWang, D-
dc.contributor.authorYang, S-
dc.contributor.authorWang, DZ-
dc.identifier.citationThe 2008 IEEE Congress on Evolutionary Computation, Hong Kong: 2967 - 2974, 01 - 06 Jun 2008en_US
dc.descriptionThis article is posted here with permission of IEEE - Copyright @ 2008 IEEEen_US
dc.description.abstractIn this paper, a multi-agent based evolutionary algorithm (MAEA) is introduced to solve dynamic optimization problems. The agents simulate living organism features and co-evolve to find optimum. All agents live in a lattice like environment, where each agent is fixed on a lattice point. In order to increase the energy, agents can compete with their neighbors and can also acquire knowledge based on statistic information. In order to maintain the diversity of the population, the random immigrants and adaptive primal dual mapping schemes are used. Simulation experiments on a set of dynamic benchmark problems show that MAEA can obtain a better performance in non-stationary environments in comparison with several peer genetic algorithms.en_US
dc.description.sponsorshipThis work was suported by the Key Program of National Natural Science Foundation of China under Grant No. 70431003, the Science Fund for Creative Research Group of the National Natural Science Foundation of China under Grant No. 60521003, the National Science and Technology Support Plan of China under Grant No. 2006BAH02A09, and the Engineering and Physical Sciences Research Council of the United Kingdom under Grant No. EP/E060722/1.en_US
dc.subjectConstraint optimizationen_US
dc.subjectDiversity methodsen_US
dc.subjectEvolutionary computationen_US
dc.subjectMultiagent systemsen_US
dc.subjectSpace stationsen_US
dc.titleA multi-agent based evolutionary algorithm in non-stationary environmentsen_US
dc.typeConference Paperen_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:Publications
Computer Science
Dept of Computer Science Research Papers

Files in This Item:
File Description SizeFormat 
Fulltext.pdf345.14 kBAdobe PDFView/Open

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