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Computer Science > Neural and Evolutionary Computing

arXiv:2109.04975 (cs)
[Submitted on 10 Sep 2021]

Title:Citizen centric optimal electric vehicle charging stations locations in a full city: case of Malaga

Authors:Christian Cintrano, Jamal Toutouh, Enrique Alba
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Abstract:This article presents the problem of locating electric vehicle (EV) charging stations in a city by defining the Electric Vehicle Charging Stations Locations (EV-CSL) problem. The idea is to minimize the distance the citizens have to travel to charge their vehicles. EV-CSL takes into account the maximum number of charging stations to install and the electric power requirements. Two metaheuristics are applied to address the relying optimization problem: a genetic algorithm (GA) and a variable neighborhood search (VNS). The experimental analysis over a realistic scenario of Malaga city, Spain, shows that the metaheuristics are able to find competitive solutions which dramatically improve the actual installation of the stations in Malaga. GA provided statistically the best results.
Subjects: Neural and Evolutionary Computing (cs.NE); Machine Learning (cs.LG)
Cite as: arXiv:2109.04975 [cs.NE]
  (or arXiv:2109.04975v1 [cs.NE] for this version)
  https://doi.org/10.48550/arXiv.2109.04975
Journal reference: Published in the XIX Conference of the Spanish Association for Artificial Intelligence (CAEPIA), 2021

Submission history

From: Jamal Toutouh [view email]
[v1] Fri, 10 Sep 2021 16:19:56 UTC (20,431 KB)
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