Show simple item record

dc.contributor.authorMavrovouniotis, Michalisen
dc.contributor.authorYang, Shengxiangen
dc.date.accessioned2013-05-20T10:12:41Z
dc.date.available2013-05-20T10:12:41Z
dc.date.issued2011
dc.identifier.citationMavrovouniotis, M. and Yang, S. (2012) An immigrants scheme based on environmental information for ant colony optimization for the dynamic travelling salesman problem. In: The 10th International Conference on Artificial Evolution, Anger, October 2011. Berlin: Springer-Verlag, pp. 1-12.en
dc.identifier.isbn978-3-642-35532-5
dc.identifier.urihttp://hdl.handle.net/2086/8601
dc.description.abstractAnt colony optimization (ACO) algorithms have proved to be powerful methods to address dynamic optimization problems. However, once the population converges to a solution and a dynamic change occurs, it is difficult for the population to adapt to the new environment since high levels of pheromone will be generated to a single trail and force the ants to follow it even after a dynamic change. A good solution is to maintain the diversity via transferring knowledge to the pheromone trails. Hence, we propose an immigrants scheme based on environmental information for ACO to address the dynamic travelling salesman problem (DTSP) with traffic factor. The immigrants are generated using a probabilistic distribution based on the frequency of cities, constructed from a number of ants of the previous iteration, and replace the worst ants in the current population. Experimental results based on different DTSP test cases show that the proposed immigrants scheme enhances the performance of ACO by the knowledge transferred from the previous environment and the generation of guided diversity.en
dc.language.isoenen
dc.publisherSpringer-Verlag.en
dc.relation.ispartofseriesLecutre Notes on Computer Science;Vol. 7401
dc.titleAn immigrants scheme based on environmental information for ant colony optimization for the dynamic travelling salesman problem.en
dc.typeArticleen
dc.identifier.doihttp://dx.doi.org/10.1007/978-3-642-35533-2_1
dc.researchgroupCentre for Computational Intelligenceen
dc.peerreviewedYesen
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record