Efficient Algorithm for Large Scale Electric Vehicle Routing Problem With Charging Capacity Constraint

This paper proposes a very efficient algorithm for large scale Electric Vehicle Routing Problem (EVRP) with charging capacity constraint of charging facilities which has not been properly addressed yet. EVRP is to jointly optimize the sequence of serving a set of transportation tasks and the charging schedule for a fleet of electric vehicles (EVs) under the constraints on the State of Charge (SOC) of battery. EVRP has gained intensive attention in recent years, yet, it is a typical mixed integer programming (MIP), which is NP-hard thus intractable for large scale cases. Meanwhile, the maximal power capacity constraint of charging facilities is very important in practice, but has not been properly addressed in previous studies, because it will further complicate the computation. This paper proposes an efficient algorithm to solve large scale EVRP with power capacity constraint of charging stations. The algorithm approximates the original problem with three sequential subproblems that are all linear programming (LP), thus ensuring certain local optimality. Extensive simulations validate the efficiency of the proposed method and show that it is hundreds of times faster than solver and can solve large scale EVRP instances with 1000 tasks.