Shi, Weixuan, Wang, Nengmin, Zhou, Li ORCID: https://orcid.org/0000-0001-7132-5935 and He, Zhengwen (2025) The bi-objective mixed-fleet vehicle routing problem under decentralized collaboration and time-of-use prices. Expert Systems with Applications. ISSN 0957-4174 (Print), 1873-6793 (Online) (doi:10.1016/j.eswa.2025.126875)

PDF (Author's Accepted Manuscript) 49766 ZHOU_The_Bi-Objective_Mixed-Fleet_Vehicle_Routing_Problem_Under_Decentralized_Collaboration_And_Time-Of-Use_Prices_(AAM)_2025.pdf - Accepted Version Restricted to Repository staff only until 12 February 2026. Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (1MB) | Request a copy

Abstract

Electric vehicles (EVs) can effectively reduce transportation carbon emissions. However, their limited driving range, longer charging times, and scarce charging locations make their transportation efficiency lower compared to traditional internal combustion engine vehicles (ICEVs). A mixed fleet leverages the strengths of both vehicle types. Additionally, collaborative logistics can further enhance these strengths by improving vehicle utilization. Therefore, this study proposes a mixed-fleet model within a collaborative logistics framework to enhance transportation efficiency and balance carbon emission reductions and economic benefits. Considering the variability in charging prices, we developed a bi-objective mixed-fleet vehicle routing optimization model with time windows incorporating order selection and time-of-use electricity pricing. An ε-constraint clustering hybrid evolutionary algorithm is formulated based on the problem characteristics. Numerical experiments with standard and large-scale instances verified the efficiency and superior performance of the developed model and algorithm. Finally, a sensitivity analysis provided managerial insight.

Item Type:	Article
Uncontrolled Keywords:	decentralized collaboration; time-of-use electricity price, mixed-fleet vehicle routing problem, bi-objective optimization
Subjects:	H Social Sciences > H Social Sciences (General) H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management T Technology > TL Motor vehicles. Aeronautics. Astronautics
Faculty / School / Research Centre / Research Group:	Greenwich Business School Greenwich Business School > Networks and Urban Systems Centre (NUSC) Greenwich Business School > Networks and Urban Systems Centre (NUSC) > Connected Cities Research Group (CCRG) Greenwich Business School > School of Business, Operations and Strategy
Last Modified:	14 Feb 2025 16:45
URI:	http://gala.gre.ac.uk/id/eprint/49766

Actions (login required)

View Item

Downloads