Joint optimization of infrastructure deployment and fleet operations for an electric carsharing system by considering multi-type vehicles

Electric carsharing (ECS) is considered an effective option to alleviate resource and environmental issues in urban transportation. In this study, we develop a mixed-integer optimization model to jointly optimize infrastructure deployment (station construction and fleet configuration) and fleet oper...

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Vydáno v:Journal of cleaner production Ročník 414; s. 137681
Hlavní autoři: Sai, Qiuyue, Bi, Jun, Zhao, Xiaomei, Guan, Wei, Lu, Chaoru
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 15.08.2023
Témata:
algorithms
China
Electric carsharing
energy
energy conservation
Fleet operations
infrastructure
Infrastructure deployment
Logic-based benders decomposition algorithm
Multiple-type electric vehicles
transportation
China
Logic-based benders decomposition algorithm
Infrastructure deployment
Multiple-type electric vehicles
Fleet operations
Electric carsharing
ISSN:0959-6526, 1879-1786
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Shrnutí:Electric carsharing (ECS) is considered an effective option to alleviate resource and environmental issues in urban transportation. In this study, we develop a mixed-integer optimization model to jointly optimize infrastructure deployment (station construction and fleet configuration) and fleet operations (vehicle assignment and charging strategy) for the ECS to maximize profits. The model further considers users’ diversified demands and incorporates multi-type electric vehicles into the problem formulation. The user-based assignment and on-demand charging strategy are also integrated into the model to improve the operational efficiency. A specialized logic-based Benders decomposition algorithm is customized to effectively solve the model. A real-life case in Lanzhou, China, is presented to demonstrate the proposed methods. Results indicate that the model has better performance and can increase profits by 20% compared with conventional methods, as hybrid fleet deployment is more energy-saving and can save up to 10% of the energy costs compared with a homogeneous fleet.
Bibliografie:ObjectType-Article-1
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ISSN:0959-6526
1879-1786
DOI:10.1016/j.jclepro.2023.137681