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 
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