An enhanced evolutionary method for routing a fleet of electric modular vehicles

• Published in: 2019 6th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS) pp. 1 - 9
• Main Authors: Rezgui, Dhekra, Aggoune-Mtalaa, Wassila, Bouziri, Hend, Chaouachi-Siala, Jouhaina
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-06-2019
• Subjects: Batteries; Delays; electric modular vehicles; evolutionary algorithms; Minimization; Planning; Routing; State of charge; Urban logistics; vehicle routing problem; Vehicles
• DOI: 10.1109/MTITS.2019.8883377

The adoption of electric vehicles are an environmental friendly initiative and a cost-effective opportunity because the number of these vehicles in the globe would be over 35 million by 2022. However, planning the routes of electric vehicles for timely delivery of goods, involves to take into account the limited energy which may lead the drivers to detour from the initial plan for recharging the batteries. In this work, the studied vehicles are modular. It means that they consist of an innovative system with one cabin for the driver and one or more modules for the goods. The research problem arising when planning the routes of such vehicles is recent. It is a particular routing problem (VRP) where the objective is the minimization of all the costs with some adding constraints linked with the recharges and the nature of the vehicles which are composed of modules. Therefore, the best current methods capable of addressing efficiently the VRP have been investigated. In this work, we propose to hybridize the population based evolutionary schema with two possible local search procedures. An intensive phase of experiments is operated to compare the approaches and show the usefulness of using the electric modules for freight delivery.