Joint optimisation of drone routing and battery wear for sustainable supply chain development: a mixed-integer programming model based on blockchain-enabled fleet sharing

Tan, Kim Hua; Xia, Yang; Zeng, Wenjia; Xing, Xinjie; Zhan, Yuanzhu; Kumar, Ajay

Abstract

Alongside the rise of ‘last-mile’ delivery in contemporary urban logistics, drones have demonstrate commercial potential, given their outstanding triple-bottom-line performance. However, as a lithium-ion battery-powered device, drones’ social and environmental merits can be overturned by battery recycling and disposal. To maintain economic performance, yet minimise environmental negatives, fleet sharing is widely applied in the transportation field, with the aim of creating synergies within industry and increasing overall fleet use. However, if a sharing platform’s transparency is doubted, the sharing ability of the platform will be discounted. Known for its transparent and secure merits, blockchain technology provides new opportunities to improve existing sharing solutions. In particular, the decentralised structure and data encryption algorithm offered by blockchain allow every participant equal access to shared resources without undermining security issues. Therefore, this study explores the implementation of a blockchain-enabled fleet sharing solution to optimise drone operations, with consideration of battery wear and disposal effects. Unlike classical vehicle routing with fleet sharing problems, this research is more challenging, with multiple objectives (i.e., shortest path and fewest charging times), and considers different levels of sharing abilities. In this study, we propose a mixed-integer programming model to formulate the intended problem and solve the problem with a tailored branch-and-price algorithm. Through extensive experiments, the computational performance of our proposed solution is first articulated, and then the effectiveness of using blockchain to improve overall optimisation is reflected, and a series of critical influential factors with managerial significance are demonstrated.

Citation

Tan, K. H., Xia, Y., Zeng, W., Xing, X., Zhan, Y., & Kumar, A. (2023). Joint optimisation of drone routing and battery wear for sustainable supply chain development: a mixed-integer programming model based on blockchain-enabled fleet sharing. Annals of Operations Research, 327(1), 89-127. https://doi.org/10.1007/s10479-021-04459-5

• Journal Article Type: Article
• Acceptance Date: Nov 16, 2021
• Online Publication Date: Dec 10, 2021
• Publication Date: 2023-08
• Deposit Date: Jan 4, 2022
• Publicly Available Date: Jan 5, 2022
• Journal: Annals of Operations Research
• Print ISSN: 0254-5330
• Electronic ISSN: 1572-9338
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• Volume: 327
• Issue: 1
• Pages: 89-127
• DOI: https://doi.org/10.1007/s10479-021-04459-5
• Keywords: Management Science and Operations Research; General Decision Sciences
• Public URL: https://nottingham-repository.worktribe.com/output/7164793
• Publisher URL: https://link.springer.com/article/10.1007%2Fs10479-021-04459-5