The electric vehicle routing problem with capacitated charging stations

Aurélien Froger (1, 2) , Ola Jabali (3) , Jorge E. Mendoza (4) , Gilbert Laporte (4, 5)

1 IMB - Institut de Mathématiques de Bordeaux
2 Realopt - Reformulations based algorithms for Combinatorial Optimization
3 POLIMI - Politecnico di Milano [Milan]
4 HEC Montréal - HEC Montréal
5 University of Bath [Bath]

Much of the existing research on electric vehicle routing problems (E-VRPs) assumes that the charging stations (CSs) can simultaneously charge an unlimited number of electric vehicles, but this is not the case. In this research, we investigate how to model and solve E-VRPs taking into account these capacity restrictions. In particular, we study an E-VRP with non-linear charging functions, multiple charging technologies, en route charging, and variable charging quantities, while explicitly accounting for the capacity of CSs expressed in the number of chargers. We refer to this problem as the E-VRP with non-linear charging functions and capacitated stations (E-VRP-NL-C). This problem advances the E-VRP literature by considering the scheduling of charging operations at each CS. We first introduce two mixed integer linear programming formulations showing how CS capacity constraints can be incorporated into E-VRP models. We then introduce an algorithmic framework to the E-VRP-NL-C, that iterates between two main components: a route generator and a solution assembler. The route generator uses an iterated local search algorithm to build a pool of high-quality routes. The solution assembler applies a branch-and-cut algorithm to select a subset of routes from the pool. We report on computational experiments comparing four different assembly strategies on a large and diverse set of instances. Our results show that our algorithm deals with the CS capacity constraints effectively. Furthermore, considering the well-known uncapacitated version of the E-VRP-NL-C, our solution method identifies new best-known solutions for 80 out of 120 instances.

Mots clés: Matheuristic; Mixed integer linear programming; Electric vehicle routing; Non-linear charging function; Synchronization constraints; Iterated local search; Branch-and-cut; non-linear charging function; synchronization constraints; mixed integer linear programming; matheuristic; iterated local search; branch-and-cut

Domaines: Recherche opérationnelle [math.OC]

Aurélien Froger, Ola Jabali, Jorge E. Mendoza, Gilbert Laporte. The electric vehicle routing problem with capacitated charging stations. Transportation Science, 2022, 56 (2), pp.460-482. ⟨10.1287/trsc.2021.1111⟩. ⟨hal-02386167v3⟩