Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/5823
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dc.contributor.authorMavrovouniotis, M-
dc.contributor.authorYang, S-
dc.date.accessioned2011-09-19T14:47:30Z-
dc.date.available2011-09-19T14:47:30Z-
dc.date.issued2010-
dc.identifier.citation11th International Conference on Parallel Problems Solving from Nature (PPSN XI), Part II, Kraków, Poland, 6239: 371 - 380, 2010-09-11 - 2010-09-15en_US
dc.identifier.isbn3-642-15870-6-
dc.identifier.isbn978-3-642-15870-4-
dc.identifier.issn0302-9743-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/5823-
dc.descriptionThis is the post-print version of this article. The official published version can be accessed from the link below - Copyright @ 2010 Springer-Verlagen_US
dc.description.abstractIn recent years, there has been a growing interest in addressing dynamic optimization problems (DOPs) using evolutionary algorithms (EAs). Several approaches have been developed for EAs to increase the diversity of the population and enhance the performance of the algorithm for DOPs. Among these approaches, immigrants schemes have been found beneficial for EAs for DOPs. In this paper, random, elitismbased, and hybrid immigrants schemes are applied to ant colony optimization (ACO) for the dynamic travelling salesman problem (DTSP). The experimental results show that random immigrants are beneficial for ACO in fast changing environments, whereas elitism-based immigrants are beneficial for ACO in slowly changing environments. The ACO algorithm with hybrid immigrants scheme combines the merits of the random and elitism-based immigrants schemes. Moreover, the results show that the proposed algorithms outperform compared approaches in almost all dynamic test cases and that immigrant schemes efficiently improve the performance of ACO algorithms in DTSP.en_US
dc.description.sponsorshipThis work was supported by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1.en_US
dc.language.isoenen_US
dc.publisherSpringer-Verlagen_US
dc.subjectAnt colony optimizationen_US
dc.subjectImmigrants schemesen_US
dc.subjectDynamic optimizationen_US
dc.titleAnt colony optimization with immigrants schemes in dynamic environmentsen_US
dc.typeConference Paperen_US
dc.identifier.doihttp://dx.doi.org/10.1007/978-3-642-15871-1_38-
pubs.place-of-publicationBerlin/Heidelberg-
pubs.organisational-data/Brunel-
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

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