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Article type: Research Article
Authors: Liang, Bingjiea; * | Bi, Juna | Ran, Bina; b
Affiliations: [a] School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China | [b] Joint Research Institute on Internet of Mobility, Southeast University and University of Wisconsin-Madison, Southeast University, Nanjing, China
Correspondence: [*] Corresponding author. Bingjie Liang, School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China. E-mail: bjliang@bjtu.edu.cn.
Abstract: Due to uncertain factors such as weather, large-scale flight delays will occur on the ground at the airport. A reasonable and effective flight sequence can make the airport resume regular operation as soon as possible. However, limited shuttle bus resources will limit the execution of the flight sequence plan. In order to provide decision support for airport authorities, we establish an integrated optimization model for flight sequences that consider shuttle bus resources. The objective function comprehensively considers the operational losses, airline profit losses, and loss of passenger time value. Then we design a multi-chromosome genetic algorithm to solve the model according to the characteristics of the integration problem. In addition, a simulation experiment is conducted based on the data from Yunnan Kunming Changshui International Airport. The simulation experiment results show that compared with the current first-come-first-served (FCFS) strategy, the algorithm reduces the overall loss caused by delays by 7.03%. The results of the simulation example verify the effectiveness of the proposed model and algorithm.
Keywords: Large-scale flight delays, integrated optimization model, shuttle bus dispatch, multi-chromosome genetic algorithm, FCFS
DOI: 10.3233/JIFS-231253
Journal: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 3165-3179, 2023
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