Research on Logistics Path Optimization for a Two-Stage Collaborative Delivery System Using Vehicles and UAVs

Qiqian Zhang (), Xiao Huang, Honghai Zhang and Chunyun He
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Qiqian Zhang: College of Civil Aviation, Nanjing University of Aeronautics & Astronautics, Nanjing 211106, China
Xiao Huang: College of Civil Aviation, Nanjing University of Aeronautics & Astronautics, Nanjing 211106, China
Honghai Zhang: College of Civil Aviation, Nanjing University of Aeronautics & Astronautics, Nanjing 211106, China
Chunyun He: College of Civil Aviation, Nanjing University of Aeronautics & Astronautics, Nanjing 211106, China

Sustainability, 2023, vol. 15, issue 17, 1-20

Abstract: A two-stage planning model for the carrier–vehicle problem with drone (CVP-D) is established in this paper, with the objective of minimizing the delivery time of the drone and the distance traveled by the truck while considering the impact of payload on the drone flight distance. Firstly, based on the customer coordinates, an improved K-Means ++ clustering algorithm is designed to plan the vehicle stopping points, and the vehicle departs from the warehouse to traverse all stopping points in order. Based on the vehicle stopping points, a multi-chromosome genetic algorithm is designed to optimize the vehicle driving path. Then, the drone route is optimized without considering the no-fly zone. Finally, the real data of Jiangsu Province are introduced as a case study to calculate the cost and total time required before and after improvement. The results showed an approximate savings of 16% in time and 19% in cost.

Keywords: air transportation; urban air mobility; collaborative delivery system; K-Means ++ cluster algorithm; multi-chromosome genetic algorithm (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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