Chapter
Jul 2, 2019
An Optimization Method for Strategy Flight Schedule to Reduce Delays
Authors: Yumeng Ren [email protected], Weili Zeng [email protected], Wenbin Wei [email protected], Jing Yu [email protected], and Lijing Chen [email protected]Author Affiliations
Publication: CICTP 2019
Abstract
Strategic flight planning is an important part of air traffic flow management. Currently, almost all flight schedules in coordinating airports in China do not satisfy one or more operational requirements, meaning that the distribution of flight schedules is unreasonable, and runway or corridor capacity can frequently not be satisfied, which results in delays. This paper proposes a data-driven strategic flight schedule optimization model to reduce unnecessary flight delays by fine-tuning flight schedules under CAAC guidelines and operational rules. The objective function of the proposed model minimizes operational delay in order to reduce delays while satisfying the airlines’ requests. The model complies with basic CAAC requirements and with corridor capacity constraints determined by historical operational data. The proposed model is applied to two busy double-runway airports: Lukou with four corridors and Xiaoshan with three. Simulation experiments show that the proposed method can reduce delays to no more than 30 min.
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© 2019 American Society of Civil Engineers.
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Published online: Jul 2, 2019
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College of Civil Aviation, Nanjing Univ. of Aeronautics and Astronautics, Jiangjun Rd. No. 29, Nanjing 211106, China. E-mail: [email protected]
College of Civil Aviation, Nanjing Univ. of Aeronautics and Astronautics, Jiangjun Rd. No. 29, Nanjing 211106, China. E-mail: [email protected]
Dept. of Aviation and Technology, San Jose State Univ., One Washington Square, San Jose, CA 95192. E-mail: [email protected]
College of Civil Aviation, Nanjing Univ. of Aeronautics and Astronautics, Jiangjun Rd. No. 29, Nanjing 211106, China. E-mail: [email protected]
College of Civil Aviation, Nanjing Univ. of Aeronautics and Astronautics, Jiangjun Rd. No. 29, Nanjing 211106, China. E-mail: [email protected]
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