Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/30811
Title: | Solving the Electric Capacitated Vehicle Routing Problem with Cargo Weight | Authors: | Mavrovouniotis, Michalis Li, Changhe Ellinas, Georgios Polycarpou, Marios M. |
Major Field of Science: | Engineering and Technology | Field Category: | Electrical Engineering - Electronic Engineering - Information Engineering | Keywords: | ant colony optimization;capacitated vehicle routing problem;Electric vehicle | Issue Date: | 1-Jan-2022 | Source: | 022 IEEE Congress on Evolutionary Computation, CEC 2022, Padua, Italy, 18 - 23 July 2022 | Conference: | 2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings | Abstract: | Electric vehicle routing problems are challenging variations of the traditional vehicle routing problem which incorporate the possibility of electric vehicle (EV) recharging at any station, while satisfying the delivery demands of customers. This work addresses the recently formulated capacitated vehicle routing problem (E-CVRP) with variable energy consumption rate. In particular, the cargo weight, which is one of the main factors affecting the energy consumption rate of EVs, is considered (i.e., the heavier the EV the higher the rate). As a solution method, an ant colony optimization algorithm with a local search heuristic is developed. Experiments are conducted on a recently generated benchmark set of E-CVRP instances demonstrating that the performance of the proposed technique improves on the best known so far solutions. | URI: | https://hdl.handle.net/20.500.14279/30811 | ISBN: | 9781665467087 | DOI: | 10.1109/CEC55065.2022.9870383 | Rights: | © IEEE | Type: | Conference Papers | Affiliation : | University of Cyprus China University of Geosciences |
Appears in Collections: | Άρθρα/Articles |
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