Driven by new policies and regulations concerning emissions of greenhouse gases from the transportation sector, battery-electric trucks (BETs) are considered one of the promising solutions to sustainable freight transportation. However, due to their constraints of vehicle range and charging time, BET fleet operations (e.g., dispatching, scheduling, routing) will need to be radically changed compared to a regular (diesel-powered) truck fleets. This project will address the dispatching problem of a generalized BET fleet, in the form of an (electric) vehicle routing problem (VRP) with pick-up and delivery windows. Since the BET fleet dispatching problem is sufficiently complex, existing approaches are not solvable for large fleets in a computation ally efficient manner. To overcome these limitations, the researchers propose a hierarchical strategy, which incorporates dispatching zone partitioning (at a high level) and metaheuristics-based vehicle scheduling/routing to optimize the itineraries of the BET fleet (at the lower level) in terms of operational costs. The proposed algorithm considers the fleet size, variations in the BET’s all electric range, the BET’s cargo capacity, availability of charging facilities/capabilities, and pickup/drop-off sequence. Furthermore, the researchers will apply the proposed strategy to real-world fleet dispatching scenarios and compare its performance with the baseline strategies deployed by the logistics company.
