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Institutional Repository [SANDBOX]
Technical University of Crete
Technical University of Crete
EN
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EL
| URI | http://purl.tuc.gr/dl/dias/65085D16-B437-4871-80F3-D93F5F0A4534 | - |
| Identifier | https://doi.org/10.1016/j.cor.2021.105397 | - |
| Identifier | https://www.sciencedirect.com/science/article/pii/S0305054821001647 | - |
| Language | en | - |
| Extent | 20 pages | en |
| Title | A hybrid ant colony optimization-variable neighborhood descent approach for the cumulative capacitated vehicle routing problem | en |
| Creator | Kyriakakis Nikolaos-Antonios | en |
| Creator | Κυριακακης Νικολαος-Αντωνιος | el |
| Creator | Marinaki Magdalini | en |
| Creator | Μαρινακη Μαγδαληνη | el |
| Creator | Marinakis Ioannis | en |
| Creator | Μαρινακης Ιωαννης | el |
| Publisher | Elsevier | en |
| Content Summary | In this paper, we present two swarm intelligence algorithms for the solution of the Cumulative Capacitated Vehicle Routing Problem. In particular, two hybrid algorithms of the Ant Colony Optimization family have been implemented, the Ant Colony System-Variable Neighborhood Decent and the Max-Min Ant System-Variable Neighborhood Decent. In this novel implementation, the ant-solution population, in both algorithms, is generated by applying local search operators on a single solution generated by the ant transition rules. This method of generating the population is compared to the traditional ACO population generation method. Their effectiveness is tested against well known benchmark instances in the literature and the results are compared to other approaches. The Ant Colony System-Variable Neighborhood Decent provided the best results among the two implemented versions and was able to find a new best known solution for two instances. Overall, on the 112 instances tested, best known solutions were reached in 92 of them. From the 20 instances in which the best known solution was not reached, 19 are instances with over 220 customers. The average gap from the best known solution in those instances is 0.35% and the maximum gap is 0.98%. | en |
| Type of Item | Peer-Reviewed Journal Publication | en |
| Type of Item | Δημοσίευση σε Περιοδικό με Κριτές | el |
| License | http://creativecommons.org/licenses/by/4.0/ | en |
| Date of Item | 2023-04-10 | - |
| Date of Publication | 2021 | - |
| Subject | Cumulative capacitated vehicle routing problem | en |
| Subject | Ant colony optimization | en |
| Subject | Max-min ant system | en |
| Subject | Ant colony system | en |
| Subject | Variable neighborhood decent | en |
| Bibliographic Citation | N. A. Kyriakakis, M. Marinaki, and Y. Marinakis, “A hybrid ant colony optimization-variable neighborhood descent approach for the cumulative capacitated vehicle routing problem,” Comput. Oper. Res., vol. 134, Oct. 2021, doi: 10.1016/j.cor.2021.105397. | en |
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