A memetic algorithm for fleet size and mix vehicle routing problems with electric modular vehicles. (15th July 2019)

• Record Type: Journal Article
• Authors: Rezgui, Dhekra; Siala, Jouhaina Chaouachi; Aggoune-Mtalaa, Wassila; Bouziri, Hend
• Is Part Of: International journal of intelligent enterprise. Volume 6:Number 2/4(2019)
• Page Start: 138
• Page End: 156
• Publication Date: 2019-07-15
• Subjects: urban logistics -- vehicle routing problem -- VRP -- metaheuristics -- electric modular vehicles -- EMVs; Organizational learning -- Periodicals; Knowledge management -- Periodicals; Business intelligence -- Periodicals; Business enterprises -- Design -- Periodicals; Organizational effectiveness -- Periodicals; 658.005
• Languages: English
• ISSNs: 1745-3232

Abstract

This work deals with an extension of the well-known vehicle routing problem with time windows (VRPTW), where the fleet consists of electric modular vehicles (EMVs). The main drawback of managing electric vehicles is that they have a limited range. Here the vehicles are modular which means that payload modules are carried by a cabin module and can be detached at certain customer locations allowing the rest of the vehicle to continue the tour. This can also permit to recharge the battery of some modules to further capitalise on the gained energy. To tackle the resulting research problem, a comprehensive mathematical formulation is proposed to take into account the multiple constraints linked with the modularity, the electric charging, time windows to serve the customers and capacity issues. Due to the NP-hardness of the problem, a memetic algorithm is implemented and tested for designing good quality solutions in reasonable computational times. Extensive computational experiments carried out on some benchmark instances show the effectiveness of both the problem formulation and the memetic algorithm.