Two-stage heuristic algorithm for vehicle-drone collaborative delivery and pickup based on medical supplies resource allocation

• Published in: Journal of King Saud University - Computer and Information Sciences
• Main Authors: Yuhang Han, Miaohan Zhang, Pan Nan, Jianing Cao, Qi Huang, Xiao Ye, Zhaolei He
• Format: Article in Journal/Newspaper
• Language: English
• Published: Elsevier 2023
• Subjects: Joint vehicle-UAV delivery; Medical supplies distribution; Forward and reverse logistics; Hybrid neighborhood search; Beluga whale optimization algorithm; Electronic computers. Computer science; QA75.5-76.95; Beluga; Beluga whale; Beluga*
• Online Access: https://doi.org/10.1016/j.jksuci.2023.101811; https://doaj.org/article/9be9f5f249724367a7d960e6906a6f8f

This paper aims to optimize medical material distribution in closed community logistics networks during sudden outbreaks with a focus on efficient waste collection and reduced consumable distribution time. First, considering the costs of UAV trajectory distribution, impact, threat, and other costs, a forward and reverse scheduling model with time windows for joint multi-distribution center material distribution and waste anti-epidemic materials collection vehicle-UAV is established. Meanwhile, a two-stage metaheuristic algorithm is proposed in this paper. In the first stage of the solution algorithm, we design the multi-strategy guided adaptive differential evolution (MSGA-DE) to plan the multi-UAV cooperative distribution situation in a 3D environment. In the second stage, an improved beluga whale optimization based on hybrid neighborhood search (HNS-IBWO) is combined to solve the vehicle-UAV scheduling and distribution problem. Furthermore, comparing with various cross-validation algorithms, it validates the superiority of MSGA-DE in solving UAV trajectory issues and the convergence speed and accuracy of HNS-IBWO for high-latitude complex optimizations. Finally, a simulation in a closed Shanghai community validates the proposed model. Results demonstrate its effectiveness, especially in terms of convergence, multi-objective search, and global search capabilities when compared to existing algorithms. This offers an efficient solution for vehicle-UAV scheduling in unforeseen epidemic-related closures.