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https://hdl.handle.net/20.500.14279/30810| Title: | A Multiple Ant Colony System for the Electric Vehicle Routing Problem with Time Windows | Authors: | Mavrovouniotis, Michalis Ellinas, Georgios Li, Changhe Polycarpou, Marios M. |
Major Field of Science: | Engineering and Technology | Field Category: | Electrical Engineering - Electronic Engineering - Information Engineering | Keywords: | ant colony optimization;Electric vehicle;vehicle routing problem with time windows | Issue Date: | 4-Dec-2022 | Source: | 2022 IEEE Symposium Series on Computational Intelligence, SSCI 2022, Singapore, Asia, 4 - 7 December 2022 | Conference: | Proceedings of the 2022 IEEE Symposium Series on Computational Intelligence, SSCI 2022 | Abstract: | Ant colony optimization (ACO) has been found to be useful on several vehicle routing problem variations. In this work, ACO is applied to the electric vehicle routing problem with time windows (E-VRPTW). The E-VRPTW has a hierarchical multiple objective function, which is to minimize the number of electric vehicles and the total distance traveled. A multiple ACO is applied to E-VRPTW in which two colonies cooperate to minimize the objectives in parallel. A local search is embedded in ACO to improve the quality of the output. The experimental results on a set of benchmark instances show that the multiple ACO is competitive with existing methods. | URI: | https://hdl.handle.net/20.500.14279/30810 | ISBN: | 9781665487689 | DOI: | 10.1109/SSCI51031.2022.10022257 | Rights: | © IEEE | Type: | Conference Papers | Affiliation : | University of Cyprus China University of Geosciences |
| Appears in Collections: | Άρθρα/Articles |
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