Optimization of hybrid delivery by vehicle and drones

• Published in: Electronic commerce research and applications 2024-07, Vol.66, p.101411, Article 101411
• Main Authors: Gu, Qiuchen, Fan, Tijun, Han, Wanke
• Format: Article
• Language: English
• Subjects: Drone; Hybrid delivery by vehicle and drones; Last-mile delivery
• ISSN: 1567-4223; 1873-7846
• DOI: 10.1016/j.elerap.2024.101411

•We formulate MILP model for hybrid delivery by vehicle and drones considering both cyclic sorties and forward sorties.•We adopt set covering for the selection of vehicle stops.•We introduce a customized hybrid genetic search with adaptive diversity control (HGSADC) for the arrangement of drone sorties. In this paper, we introduce the optimization of hybrid delivery by vehicle and drones. Hybrid delivery by vehicle and drones is advantageous for improving O2O last-mile delivery efficiency. However, vehicle stop selection and drone delivery sortie arrangement are challenging in the optimization of hybrid delivery by vehicle and drones because cyclic sorties and forward sorties jointly influence the total makespan of the delivery. To minimize the delivery makespan, an MILP model for hybrid delivery is formulated considering both the cyclic sorties and forward sorties of drones. In the proposed model, the intertwined influences of the flight times of cyclic and forward sorties and their further effects on total delivery makespan are depicted. Additionally, we introduce an ACO based on set covering for the selection of vehicle stops and a customized HGSADC for the arrangement of drone sorties. A study based on a simulated case and experiments based on 40 generated instances at different scales are explored to assess the optimization of hybrid delivery by vehicle and drones.