An Innovative Multi-Objective Rescheduling System for Mitigating Pandemic Spread in Aviation Networks

Yujie Yuan, Yantao Wang, Xiushan Jiang () and Chun Sing Lai ()
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Yujie Yuan: School of Air Traffic Management, Civil Aviation University of China, Tianjin 300300, China
Yantao Wang: School of Air Traffic Management, Civil Aviation University of China, Tianjin 300300, China
Xiushan Jiang: School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
Chun Sing Lai: Department of Electronic and Electrical Engineering, Brunel University London, London UB8 3PH, UK

Clean Technol., 2024, vol. 6, issue 1, 1-16

Abstract: The novel coronavirus outbreak has significantly heightened environmental costs and operational challenges for civil aviation airlines, prompting emergency airport closures in affected regions and a substantial decline in ridership. The consequential need to reassess, delay, or cancel flight itineraries has led to disruptions at airports, amplifying the risk of disease transmission. In response, this paper proposes a spatial approach to efficiently address pandemic spread in the civil aviation network. The methodology prioritizes the use of a static gravity model for calculating route-specific infection pressures, enabling strategic flight rescheduling to control infection levels at airports (nodes) and among airlines (edges). Temporally, this study considers intervals between takeoffs and landings to minimize crowd gatherings, mitigating the novel coronavirus transmission rate. By constructing a discrete space–time network for irregular flights, this research generates a viable set of routes for aircraft operating in special circumstances, minimizing both route-specific infection pressures and operational costs for airlines. Remarkably, the introduced method demonstrates substantial savings, reaching almost 53.4%, compared to traditional plans. This showcases its efficacy in optimizing responses to pandemic-induced disruptions within the civil aviation network, offering a comprehensive solution that balances operational efficiency and public health considerations in the face of unprecedented challenges.

Keywords: rescheduling; discrete spatiotemporal network; infectious pressure; coronavirus pandemic (search for similar items in EconPapers)
JEL-codes: Q2 Q3 Q4 Q5 (search for similar items in EconPapers)
Date: 2024
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