The charger location problem with routing and driver working hours for long-haul electric heavy-duty trucks

• A charger location problem with routing is proposed for long-haul electric trucks. • HOS regulation and multiple charger power levels are embedded in the model. • A communication-time-expanded network is built via temporal discretization. • Preprocessing removes superfluous nodes, arcs, and constraints to improve tractability. • Computational tests assess preprocessing effectiveness on real network. The limited network of chargers for electric heavy-duty trucks (eHDTs) hinders a widespread adoption due to their shorter operating range compared to diesel engines. The charger location problem seeks to determine the optimal number and location of chargers in a transportation network to support efficient eHDT logistics operations. Moreover, commercial drivers’ hours of service (HOS) are regulated by law, requiring careful planning of driving, breaks, and rest periods. In this context, effective vehicle scheduling and routing are crucial to increasing punctuality and safety in road freight transport. Neglecting these operational aspects in the charger location problem can lead to suboptimal or even infeasible decisions. The aim of this paper is to develop, model and solve the charger location problem with routing and driver’s working hours. The decisions include the long-haul electric vehicle routing, and the scheduling of drivers respecting HOS requirements by determining the locations, types and number of chargers. The problem is modeled by transforming the road network into a communication-time-expanded network through a temporal discretization process. We also present two mechanisms to reduce the model size. We conduct extensive numerical experiments in order to demonstrate the efficiency of the proposed optimization methods and to evaluate the impact of several features on the routing and scheduling of the eHDTs.