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Electric Vehicle Routing Problem: Literature Review, Instances and Results with a Novel Ant Colony Optimization Method
School of Engineering, University of the Aegean, Management and Decision Engineering Laboratory, Chios, Greece.
Université de Sherbrooke, Multiobjective Optimization REsearch Lab (MORE Lab), Sherbrooke, QC, Canada.ORCID iD: 0000-0002-1319-513X
Tecnalia, Basque Research and Technology Alliance (BRTA), Derio, Spain.
School of Engineering, University of the Aegean, Management and Decision Engineering Laboratory, Chios, Greece.
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2022 (English)In: 2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings, IEEE, 2022Conference paper, Published paper (Refereed)
Abstract [en]

One of the most well-known problems in combinatorial optimization is the Vehicle Routing Problem (VRP). Significant research has been done around this problem in two different perspectives: investigating new solving approaches, and studying variants of VRP which take into consideration multiple restrictions and constraints. One of such versions is the Electric Vehicle Routing Problem (EVRP), whose main objective is to find the optimal route of a fleet of electric vehicles, taking into account the locations of charging stations and the battery consumption of the mobile units. The aim of this study is threefold: (a) to perform a brief literature review on meta-heuristic approaches applied to the EVRP, (b) to offer insights on the available data instances for this problem, and (c) to discuss on the results of an experimental benchmark aimed at comparing different meta-heuristic approaches over diverse EVRP instances, including the proposal and evaluation of a novel Ant Colony Optimization approach.

Place, publisher, year, edition, pages
IEEE, 2022.
Keywords [en]
Ant Colony Optimization, Electric Vehicle Routing Problem, Meta-heuristics, Vehicle Routing Problem, Artificial intelligence, Combinatorial optimization, Electric vehicles, Fleet operations, Heuristic algorithms, Heuristic methods, Vehicle routing, Ant colony optimization methods, Battery consumption, Charging station, Literature reviews, Meta-heuristic approach, Metaheuristic, Optimal routes, Vehicle Routing Problems
National Category
Computer Sciences Mechanical Engineering
Identifiers
URN: urn:nbn:se:hj:diva-63828DOI: 10.1109/CEC55065.2022.9870373Scopus ID: 2-s2.0-85138674202ISBN: 9781665467087 (print)OAI: oai:DiVA.org:hj-63828DiVA, id: diva2:1846174
Conference
2022 IEEE Congress on Evolutionary Computation (CEC), Padua, Italy, 18-23 July 2022
Available from: 2024-03-21 Created: 2024-03-21 Last updated: 2024-03-21Bibliographically approved

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Tzanetos, Alexandros

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