Electric Vehicle Routing with Public Charging Stations

Nicholas D. Kullman (), Justin C. Goodson () and Jorge E. Mendoza ()
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Nicholas D. Kullman: Universitè de Tours, LIFAT EA 6300, CNRS, ROOT ERL CNRS 7002, 37200 Tours, France
Justin C. Goodson: Richard A. Chaifetz School of Business, Saint Louis University, St. Louis, Missouri 63103
Jorge E. Mendoza: HEC Montréal, Montréal, Québec H3T 2A7, Canada; Centre Interuniversitaire de Recherche sur les Réseaux d'Entreprise, la Logistique et le Transport (CIRRELT), Montréal, Québec H3T 1J4, Canada

Transportation Science, 2021, vol. 55, issue 3, 637-659

Abstract: We introduce the electric vehicle routing problem with public-private recharging strategy in which vehicles may recharge en route at public charging infrastructure as well as at a privately-owned depot. To hedge against uncertain demand at public charging stations, we design routing policies that anticipate station queue dynamics. We leverage a decomposition to identify good routing policies, including the optimal static policy and fixed-route-based rollout policies that dynamically respond to observed queues. The decomposition also enables us to establish dual bounds, providing a measure of goodness for our routing policies. In computational experiments using real instances from industry, we show the value of our policies to be within 10% of a dual bound. Furthermore, we demonstrate that our policies significantly outperform the industry-standard routing strategy in which vehicle recharging generally occurs at a central depot. Our methods stand to reduce the operating costs associated with electric vehicles, facilitating the transition from internal-combustion engine vehicles.

Keywords: dynamic vehicle routing; electric vehicles; fixed routes; information relaxation; information penalties; approximate dynamic programming (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ortrsc:v:55:y:2021:i:3:p:637-659

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