Application of a variable neighborhood search algorithm to a fleet size and mix vehicle routing problem with electric modular vehicles

Abstract

The emergence of new promising technologies used in electric transportation offers opportunities to achieve sustainable urban freight deliveries. In particular fleets of electric vehicles are seen as an efficient ecologic and economic transportation alternative for operating last-mile goods distribution in cities. This paper deals with the use of electric modules which can be added or removed from a freight vehicle to help gain capacity or respect delays when delivering customers. Since the electric vehicles have a limited battery capacity, they have to stop and recharge them at dedicated stations during the delivery tours. However, with the modular feature, this problem of disturbing the whole distribution process for recharging the batteries can be reduced and sometimes overlooked. This paper objective is to design and find the optimal routing strategy for a fleet of electric modular vehicles operating the last-mile delivery, with the minimal cost including the acquisition, the travel and the recharging ones. The research problem arising from the structure of the fleet can be associated with both a truck and trailer problem and a fleet size and mix vehicle routing problem with time windows using electric vehicles. This problem is presented in the first part of the article with the proposed solving procedure. More precisely, for big instances of the problem which is NP-Hard, a Variable Neighborhood Search (VNS) is designed and adapted. Experimental studies carried out on some benchmark instances show that the VNS performs impressively well in comparison with the best solving approaches of the literature.