2021/04/08 by Yiqi Zhao, Zhao, Yiqi, Teng Zeng +7
Engineering · #Electric Vehicles and Infrastructure #FOS: Mathematics #Optimization and Control (math.OC) #Transportation and Mobility Innovations #Vehicle Routing Optimization Methods
paper · pdf · doi:10.48550/arxiv.2104.03951
openalex publication_date 2021/04/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This work proposes a new modeling framework for jointly optimizing the charging network design and the logistic mobility planning for an electric vehicle fleet. Existing literature commonly assumes the existence of a single entity, the social planner, as a powerful decision maker who manages all resources. However, this is often not the case in practice. Instead of making this assumption, we specifically examine the innate noncooperative nature of two different entities involved in the planning problem. Namely, they are the charging service provider (CSP) and the fleet operator (FO). To address the strategic interaction between entities, a bilevel mixed integer program is formulated, with the CSP and FO problems expressed in the upper and lower levels respectively, in a joint decision making process. These decisions involve the CSP infrastructure siting, sizing, substation capacity upgrades, the FO fleet composition, vehicle routing, charging, and delivery assignment. To relieve computational burdens, we utilize a double loop solution architecture to iteratively reach optimality. We conduct detailed numerical studies on a synthesized small network and the simulation results reveal the unique aspects of this two entity framework. This modeling perspective can be generalized to other system design problems with two interacting agents planning and operating resources across networks.