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dc.contributor.authorMavrovouniotis, Michalisen
dc.contributor.authorYang, Shengxiangen
dc.date.accessioned2013-05-17T10:31:39Z
dc.date.available2013-05-17T10:31:39Z
dc.date.issued2012
dc.identifier.citationMavrovvouniotis, M. and Yang, S. (2012) Ant colony optimization with immigrants schemes for the dynamic vehicle routing problem. In: Applications of Evolutionary Computation EvoApplications, Málaga, April 2012. Berlin: Springer-Verlag, pp. 519-528.en
dc.identifier.isbn9783642291777
dc.identifier.urihttp://hdl.handle.net/2086/8594
dc.description.abstractAnt colony optimization (ACO) algorithms have proved to be able to adapt to dynamic optimization problems (DOPs) when they are enhanced to maintain diversity and transfer knowledge. Several approaches have been integrated with ACO to improve its performance for DOPs. Among these integrations, the ACO algorithm with immigrants schemes has shown good results on the dynamic travelling salesman problem. In this paper, we investigate ACO algorithms to solve a more realistic DOP, the dynamic vehicle routing problem (DVRP) with traffic factors. Random immigrants and elitism-based immigrants are applied to ACO algorithms, which are then investigated on different DVRP test cases. The results show that the proposed ACO algorithms achieve promising results, especially when elitism-based immigrants are used.en
dc.language.isoenen
dc.publisherSpringer-Verlag.en
dc.relation.ispartofseriesLecture Notes on Computer Science;Vol. 7248
dc.titleAnt colony optimization with immigrants schemes for the dynamic vehicle routing problem.en
dc.typeArticleen
dc.identifier.doihttp://dx.doi.org/10.1007/978-3-642-29178-4_52
dc.researchgroupCentre for Computational Intelligenceen
dc.peerreviewedYesen
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en


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