Electric vehicle routing problem with flexible deliveries

Sadati, Mir Ehsan Hesam; Akbarighadikolaei, Vahid; Çatay, Bülent

Abstract

Growing concerns about the climate change have forced governments to initiate tighter environmental regulations and tougher emission reduction targets, increasing the interest on electromobility. Logistics operators started employing electric vehicles (EVs) and must face new operational planning challenges. Moreover, with an ever-growing interest in e-commerce, parcel delivery is taking new shapes by offering flexible delivery options to the customers. To mitigate these issues, we introduce the Electric Vehicle Routing Problem with Flexible Deliveries (EVRP-FD), where the customers are served using a fleet of EVs that can recharge their batteries along their routes. In this problem, a customer may specify different delivery locations for different time windows. Our objective is to serve the customers while minimising the total travelled distance using minimum number of vehicles. We first give the mathematical model and then develop a hybrid Variable Neighbourhood Search coupled with Tabu Search by proposing new mechanisms to solve the problem effectively. Then, we verify the performance of our algorithm on instances from the literature. We also introduce new instances for the EVRP-FD and perform an extensive computational study to investigate the trade-offs associated with different operational factors. Finally, we present a case study in Nottingham, UK to provide further insights.

Citation

Sadati, M. E. H., Akbarighadikolaei, V., & Çatay, B. (2022). Electric vehicle routing problem with flexible deliveries. International Journal of Production Research, 60(13), 4268-4294. https://doi.org/10.1080/00207543.2022.2032451

• Journal Article Type: Article
• Acceptance Date: Jan 10, 2022
• Online Publication Date: Feb 15, 2022
• Publication Date: Jul 3, 2022
• Deposit Date: Feb 17, 2022
• Publicly Available Date: Feb 16, 2023
• Journal: International Journal of Production Research
• Print ISSN: 0020-7543
• Electronic ISSN: 1366-588X
• Publisher: Taylor and Francis
• Peer Reviewed: Peer Reviewed
• Volume: 60
• Issue: 13
• Pages: 4268-4294
• DOI: https://doi.org/10.1080/00207543.2022.2032451
• Keywords: Electric vehicle routing problem; flexible deliveries; variable neighborhood search; granular tabu search; recharging
• Public URL: https://nottingham-repository.worktribe.com/output/7471982
• Publisher URL: https://www.tandfonline.com/doi/full/10.1080/00207543.2022.2032451