The dial-a-ride problem with electric vehicles and battery swapping stations. (October 2018)

• Record Type: Journal Article
• Authors: Masmoudi, Mohamed Amine; Hosny, Manar; Demir, Emrah; Genikomsakis, Konstantinos N.; Cheikhrouhou, Naoufel
• Is Part Of: Transportation research. Volume 118(2018)
• Page Start: 392
• Page End: 420
• Publication Date: 2018-10
• Subjects: Electric vehicle -- Dial-a-ride problem -- Battery swapping -- Evolutionary variable neighborhood search metaheuristic algorithm; Logistics -- Periodicals; Transportation -- Periodicals; 388.011
• DOI: 10.1016/j.tre.2018.08.005
• Languages: English
• ISSNs: 1366-5545

Abstract

Highlights: A practical extension of the Dial-a-Ride Problem (DARP) is studied. Electric vehicles with battery-swap stations and a realistic energy consumption function are used. Three enhanced Evolutionary Variable Neighborhood Search algorithms are proposed and compared against each other. The proposed algorithms are competitive with the current state-of-the-art algorithm for the DARP in terms of solution quality in a reasonable computational time. Abstract: The Dial-a-Ride Problem (DARP) consists of designing vehicle routes and schedules for customers with special needs and/or disabilities. The DARP with Electric Vehicles and battery swapping stations (DARP-EV) concerns scheduling a fleet of EVs to serve a set of pre-specified transport requests during a certain planning horizon. In addition, EVs can be recharged by swapping their batteries with charged ones from any battery-swap stations. We propose three enhanced Evolutionary Variable Neighborhood Search (EVO-VNS) algorithms to solve the DARP-EV. Extensive computational experiments highlight the relevance of the problem and confirm the efficiency of the proposed EVO-VNS algorithms in producing high quality solutions.