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dc.contributor.authorMavrovouniotis, Michalisen
dc.contributor.authorYang, Shengxiangen
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.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.relation.ispartofseriesLecture Notes on Computer Science;Vol. 7248
dc.titleAnt colony optimization with immigrants schemes for the dynamic vehicle routing problem.en
dc.researchgroupCentre for Computational Intelligenceen
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en

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