Application of CMSA to the Electric Vehicle Routing Problem with Time Windows, Simultaneous Pickup and Deliveries, and Partial Vehicle Charging

Abstract

As a consequence of the growing importance of environmental issues, partially due to a negative impact of transportation activities, the use of environmentally-friendly vehicles in logistics has become one of the prominent concepts in recent years. In this line, this paper addresses a variant of the vehicle routing problem, the electric vehicle routing problem with time windows and simultaneous pickup and deliveries, which are two essential real-life constraints. Moreover, we consider partial recharging of electric vehicles at charging stations. A recent self-adaptive variant of the matheuristic “Construct, Merge, Solve & Adapt” (CMSA) is applied to solve the tackled problem. CMSA combines heuristic elements, such as the probabilistic generation of solutions, with an exact solver that is iteratively applied to sub-instances of the original problem instances. Two constructive heuristics, a Clark & Wright Savings algorithm and a sequential insertion heuristic, are probabilistically applied to generate solutions which are then subsequently merged to form a sub-instance. The numerical results show that CMSA outperforms CPLEX in the context of small problem instances. Moreover, it is shown that CMSA outperforms the heuristic algorithms when large problem instances are concerned. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.