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Τίτλος: A Multiple Ant Colony System for the Electric Vehicle Routing Problem with Time Windows
Συγγραφείς: Mavrovouniotis, Michalis 
Ellinas, Georgios 
Li, Changhe 
Polycarpou, Marios M. 
Major Field of Science: Engineering and Technology
Field Category: Electrical Engineering - Electronic Engineering - Information Engineering
Λέξεις-κλειδιά: ant colony optimization;Electric vehicle;vehicle routing problem with time windows
Ημερομηνία Έκδοσης: 4-Δεκ-2022
Πηγή: 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 
Περίληψη: 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 
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