Simultaneous electric vehicles scheduling and optimal charging in the business context: case study

Our study deals with the simultaneous Electric Vehicle Scheduling and Optimal Charging Problem (EVSCP) in the business context. More precisely, given a mixed fleet of Electric Vehicles - EVs and Combustion Engine Vehicles - CVs, a set of tours to be processed by vehicles and a charging infrastructure, the problem aims to optimize the assignment of vehicles to tours and, simultaneously, to optimize the charging of EVs in order to avoid costly and carbon-hungry peak demand periods. We consider several operational constraints mainly related to chargers, electricity grid and EVs driving range. The overall objective of this study is to provide an efficient, scalable and generic decision support tool, combining both technical and business considerations, for vehicle fleet managers that are willing to minimize their vehicles ownership costs, to reduce CO₂ emissions and to avoid EVs batteries degradation. This study is promoted in the scope of a French National Project, led by La Poste Group1, ERDF2 and seven other companies and research laboratories. This R&D project aims at designing, with a progressive approach, a smart system that manages the charging infrastructures and allows an economical and ecological sustainable deployment of EVs fleet in the business context. To solve this problem, we provide a mixed-integer linear programming formulation to model the EVSCP problem and we use CPLEX to solve real test instances. Moreover, we propose different business scenarios and extensions to our baseline model. For instance, we consider the impact of EV use on the battery health and we are interested in different charging schemes, charging infrastructure, energy mix and CO₂ emissions.