Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/30865
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Mavrovouniotis, Michalis | - |
dc.contributor.author | Yang, Shengxiang | - |
dc.date.accessioned | 2023-11-27T12:47:18Z | - |
dc.date.available | 2023-11-27T12:47:18Z | - |
dc.date.issued | 2013-01-01 | - |
dc.identifier.citation | 16th European Conference on Applications of Evolutionary Computation, EvoApplications 2013, 3 - 5 April 2013 | en_US |
dc.identifier.isbn | 9783642371912 | - |
dc.identifier.issn | 03029743 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.14279/30865 | - |
dc.description.abstract | Ant colony optimization (ACO) algorithms have proved to be able to adapt to dynamic optimization problems (DOPs) when stagnation behaviour is avoided. Several approaches have been integrated with ACO to improve its performance for DOPs. The adaptation capabilities of ACO rely on the pheromone evaporation mechanism, where the rate is usually fixed. Pheromone evaporation may eliminate pheromone trails that represent bad solutions from previous environments. In this paper, an adaptive scheme is proposed to vary the evaporation rate in different periods of the optimization process. The experimental results show that ACO with an adaptive pheromone evaporation rate achieves promising results, when compared with an ACO with a fixed pheromone evaporation rate, for different DOPs. © Springer-Verlag Berlin Heidelberg 2013. | en_US |
dc.language.iso | en | en_US |
dc.rights | © Springer-Verlag Berlin Heidelberg | en_US |
dc.subject | Dynamic routing algorithms | en_US |
dc.subject | Evaporation | en_US |
dc.subject | Adaptive scheme | en_US |
dc.subject | Ant Colony Optimization algorithms | en_US |
dc.subject | Dynamic optimization problem (DOP) | en_US |
dc.subject | Dynamic routing | en_US |
dc.subject | Evaporation rate | en_US |
dc.subject | Pheromone trails | en_US |
dc.title | Adapting the pheromone evaporation rate in dynamic routing problems | en_US |
dc.type | Conference Papers | en_US |
dc.collaboration | De Montfort University | en_US |
dc.subject.category | Computer and Information Sciences | en_US |
dc.country | United Kingdom | en_US |
dc.subject.field | Natural Sciences | en_US |
dc.relation.conference | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | en_US |
dc.identifier.doi | 10.1007/978-3-642-37192-9_61 | en_US |
dc.identifier.scopus | 2-s2.0-84875637343 | en |
dc.identifier.url | https://api.elsevier.com/content/abstract/scopus_id/84875637343 | en |
dc.contributor.orcid | #NODATA# | en |
dc.contributor.orcid | #NODATA# | en |
dc.relation.volume | 7835 LNCS | en_US |
cut.common.academicyear | 2013-2014 | en_US |
item.grantfulltext | none | - |
item.openairecristype | http://purl.org/coar/resource_type/c_c94f | - |
item.fulltext | No Fulltext | - |
item.languageiso639-1 | en | - |
item.cerifentitytype | Publications | - |
item.openairetype | conferenceObject | - |
crisitem.author.orcid | 0000-0002-5281-4175 | - |
Appears in Collections: | Άρθρα/Articles |
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