In recent years, electric vehicle routing problems (E-VRPs) have received an constantly-increasing attention from the operations research community. In a nutshell, E-VRPs extend classical routing problems to consider the limited driving range of electric vehicles. One of the key modelling aspects in E-VRPs concern the battery charging process. Indeed, E-VRP models strongly rely on assumptions about the charging function approximation. This approximation models the relationship between battery charging time and state of charge (SoC). In practice, the SoC is a concave function of the charging time. Nonetheless, in the E-VRP literature, it is usually approximated using linear functions. In this talk, we introduce and discuss the family of E-VRPs with non-linear charging function approximations (E-VRPs-NL). To motivate our research, we first present a computational study comparing (in terms of solution quality and feasibility) non-linear approximations with linear approximations commonly used in the literature. We then present models and (matheuristic) solution approaches for two different E-VRP-NL variants. The first is a more theoretical variant that allows the audience to gain insight into these new problems. The second is a real-world problem faced by Enedis, a subsidiary of french electricity giant EDF.
Jorge E. Mendoza is an Associate Professor in the Department of Computer Science at Polytech Tours and the co-director of the Operations Research, Scheduling, and Transportation research group (ERL 6305 CNRS) at the University of Tours’ Computer Science Laboratory (EA 6300). Since late 2015 Dr. Mendoza is also the head of Electric Vehicle Routing Optimization (e-VRO), a 4-year research program funded by the French national research agency (ANR). He holds a B.Sc. (2004) in Industrial Engineering from Universidad Industrial de Santander (Colombia), a M.Sc. (2007) in Industrial Engineering from Universidad de los Andes (Colombia), and a Ph.D. (2009) in Computer Science from Université de Nantes (France) and Universidad de los Andes. His research interests include the design, development, and application of optimization techniques to: transportation science, logistics, production planning, and scheduling. Dr. Mendoza is also interested in the development of open-source software for operations research. His research has been published in Transportation Science, Decision Support Systems, European Journal of Operational Research, Computers & Operations Research, Journal of Heuristics, Transportation Research Parts B and C, Journal of Scheduling, Optimization Letters, 4OR, and a number for international conferences.