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DC Field | Value | Language |
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dc.contributor.author | Mavrovouniotis, M | - |
dc.contributor.author | Yang, S | - |
dc.date.accessioned | 2011-09-19T14:47:30Z | - |
dc.date.available | 2011-09-19T14:47:30Z | - |
dc.date.issued | 2010 | - |
dc.identifier.citation | 11th International Conference on Parallel Problems Solving from Nature (PPSN XI), Part II, Kraków, Poland, 6239: 371 - 380, 2010-09-11 - 2010-09-15 | en_US |
dc.identifier.isbn | 3-642-15870-6 | - |
dc.identifier.isbn | 978-3-642-15870-4 | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/5823 | - |
dc.description | This is the post-print version of this article. The official published version can be accessed from the link below - Copyright @ 2010 Springer-Verlag | en_US |
dc.description.abstract | In 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.sponsorship | This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Springer-Verlag | en_US |
dc.subject | Ant colony optimization | en_US |
dc.subject | Immigrants schemes | en_US |
dc.subject | Dynamic optimization | en_US |
dc.title | Ant colony optimization with immigrants schemes in dynamic environments | en_US |
dc.type | Conference Paper | en_US |
dc.identifier.doi | http://dx.doi.org/10.1007/978-3-642-15871-1_38 | - |
pubs.place-of-publication | Berlin/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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