A bi-objective optimization model for the medical supplies' simultaneous pickup and delivery with drones. (September 2022)

• Record Type: Journal Article
• Authors: Shi, Yuhe; Lin, Yun; Li, Bo; Yi Man Li, Rita
• Is Part Of: Computers & industrial engineering. Volume 171(2022)
• Publication Date: 2022-09
• Subjects: Drone -- Public health emergencies -- Medical supplies -- Pickup and delivery -- Location routing problem; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2022.108389
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: A new solution for the medical supplies' delivery and pick-up. A bi-objective optimisation model for drone delivery problem. Pareto frontier evaluation balancing economic and safety effects. A heuristic algorithm based on NSGA-II has better solving performance. Abstract: In the COVID-19 pandemic, it is essential to transport medical supplies to specific locations accurately, safely, and promptly on time. The application of drones for medical supplies delivery can break ground traffic restrictions, shorten delivery time, and achieve the goal of contactless delivery to reduce the likelihood of contacting COVID-19 patients. However, the existing optimization model for drone delivery is cannot meet the requirements of medical supplies delivery in public health emergencies. Therefore, this paper proposes a bi-objective mixed integer programming model for the multi-trip drone location routing problem, which allows simultaneous pick-up and delivery, and shorten the time to deliver medical supplies in the right place. Then, a modified NSGA-II (Non-dominated Sorting Genetic Algorithm II) which includes double-layer coding, is designed to solve the model. This paper also conducts multiple sets of data experiments to verify the performance of modified NSGA-II. Comparing with separate pickup and delivery modes, this study demonstrates that the proposed optimization model with simultaneous pickup and delivery mode achieves a shorter time, is safer, and saves more resources. Finally, the sensitivity analysis is conducted by changing some parameters, and providing some reference suggestions for medical supplies delivery management via drones.