Overview of Flight Planning Optimization Research

LI De long, XU Hai wen, FU Qiang

Article ID: 2580
Vol 2, Issue 2, 2022
DOI: https://doi.org/10.54517/vfc.v2i2.2580
VIEWS - 2311 (Abstract)

Download PDF

Abstract

From the analysis of different time stages of flight planning optimization, flight planning optimization can be divided into three aspects: static flight planning optimization, flight planning dynamic feedback optimization based on flight delay prediction, and flight planning dynamic adjustment based on airport collaborative decision -making (A-CDM). Then, it analyzes the static scheduling and optimization of flight plans from the preparation links of flight schedules, aircraft type assignments, and flight frequencies; then uses the optimization method of delay spread prediction and data mining prediction to analyze the correlation of flight plan dynamic feedback optimization based on flight delay prediction the study. Finally, according to the complexity analysis of flight plan optimization, the development trend and future research directions of flight plan optimization are given.


Keywords

Flight planning optimization, Delay prediction, Deep learning, Airport-collaborative decision-making, Supervised learning.


References

1. Pan Weijun. Fundamentals of Air Traffic Management [M]. Second Edition. Chengdu: Southwest Jiaotong University Press, 2013:206-207.

2. Xu Haiwen. Research on the controllability of restoring abnormal flight plans [D]. Nanjing University of Aeronautics and Astronautics, 2018.

3. Wegmann H M, Hasenclever S, Michel C, et al. Models to predict operational loads of flight schedules. 1985, 56(1):27-32.

4. Dachkovsky V.Z., Pozdnyakov V.V., Yanbykh G.F.. The Decision -making Procedure in the Automated Process of Formulating a Flight Schedule. 1983, 16(20):465-470.

5. Jiang Tao, Zhu Jinfu. Research on the Benefit Analysis of Airline Network Configuration [J]. Industrial Technology and Economics, 2006 (11): 105-107.

6. Hu Minghua, Chen Aimin, Xu Xiaohao, Yuan Weidong. Research on Ground Waiting Strategy Problems with Multiple Constraints [J]. Journal of Nanjing University of Aeronautics and Astronautics, 1998 (01):3-5.

7. Christopher C. Findlay. Optimal Air Fares and Flight Frequency and Market Results. 1983, 17(1):49-66.

8. Duš, an B. Teodorovi&cacute. Flight Frequency Determination. 1983, 109(5):747-757.

9. Sze -Wei Chang, Paul Schonfeld. Optimized Schedules for Airline Routes. 2004, 130(4):412-418.

10. Zhu Jinfu. Air Transport Planning [M]. Xi'an: Northwest Polytechnical University Press, 2010.

11. Zhu Xinghui. Research on Optimization Design of Airline Flight Plans [D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2007.

12. Jiang Silu, Zhu Jinfu, Kong Mingxing, Zhou Qinyan. Optimization of Flight Frequency Based on Passenger Plan Delays [J] Journal of Wuhan University of Technology (Transportation Science and Engineering Edition), 2019, 43 (01): 136-140.

13. Zhu Xinghui, Zhu Jinfu, Gong Zaiwu. Research on aircraft type assignment models and algorithms for Chinese airlines [J]. Industrial Technology and Economics, 2007 (04): 75-77.

14. Barry C. Smith, Ellis L. Johnson. Robust Airline Fleet Assignment: Imposing Station Purity Using Station Decomposition. 2006, 40(4).

15. Oussama Aoun, Malek Sarhani, Abdellatif El Afia. Investigation of hidden markov model for the tuning of metaheuristics in airline scheduling problems. 2016, 49(3):347-352.

16. Zhu Xinghui, Zhu Jinfu, Gao Qiang. Research on Robust Aircraft Type Assignment Problem Based on Flight Purity [J]. Prediction, 2011, 30 (01): 71-74.

17. Jiang Silu. Research on Comprehensive Optimization of Flight Frequency and Model Assignment [D]. Nanjing University of Aeronautics and Astronautics, 2019.

18. Hu Minghua, Zhu Jingbo, Tian Yong. Research on the Optimization Model and Method of Multivariate Constrained Flight Schedule [J]. Journal of Nanjing University of Aeronautics and Astronautics, 2003 (03): 326-332

19. Miguel Lambelho, Mihaela Mitici, Simon Pickup, et al. Assessing strategic flight schedules at an airport using machine learning-based flight delay and cancellation predictions. 2020, 82.

20. Yufeng Tu, Michael O Ball, Wolfgang S Jank, Estimating Flight Departure Delay Distributions—A Statistical Approach With Long -Term Trend and Short -Term Pattern [J]. Journal of the American Statistical Association, 2008, 103.

21. Loo Hay Lee, Chul Ung Lee, Yen Ping Tan. A multi-objective genetic algorithm for robust flight scheduling using simulation. 2005, 177(3):1948-1968.

22. Ahmed Abdelghany, Khaled Abdelghany, Farshid Azadian. Airline flight schedule planning under competition. 2017, 87:20-39.

23. Xi Geng, Minghua Hu, Stefan Balint. Simulated Annealing Method -Based Flight Schedule Optimization in Multiairport Systems. 2020.

24. Fu Zhenyu, Xu Haiwen, Fu Qiang. Overview of Flight Delay Prediction Research [J]. Science and Innovation, 2020 (03): 1-4.

25. Liu Bo, Ye Bojia, Tian Yong, Yang Minhao. Research Review on Flight Delay Prediction Methods [J]. Aviation Computing Technology, 2019, 49 (06): 124-128.

26. Wang Nan, Yang Hongru, Zhou Jianjun, Cao Dunbo. Quantitative study on the impact of severe weather on flight delays at Urumqi Airport [J]. Drought Meteorology, 2018, 36 (04): 684-693.

27. Sun Choi,Young Jin Kim,Simon Briceno,Dimitri Mavris. Prediction of weather -induced airline delays based on machine learning algorithms [A].in:IEEE,.2016 IEEE/AIAA 35th Digital Avionics Systems Conference : [Volume 1 of 2] Pages 1-657.[C]. 2016: 1-6.

28. Su Aijing, Yang Wendong, Zhang Chong, Kong Mingxing. Simulation modeling analysis of flight operation system [J]. Journal of Harbin Institute of Technology, 2019, 51 (09): 49-55.

29. Dunbar, Michelle,Froyland, Gary,Wu, Cheng-Lung. Robust Airline Schedule Planning: Minimizing Propagated Delay in an Integrated Routing and Crewing Framework [J]. Transportation Science,2012,46(2).

30. CAO W D, HE G G. Bayesian networks analysis for sequence flight delay and propagation [J]. Journal of Computer Applications, 2009, 29(2): 606-610.

31. Weiwei Wu, Cheng-Lung Wu. Enhanced delay propagation tree model with Bayesian Network for modelling flight delay propagation. 2018, 41(3):319-335.

32. Wu Weiwei, Meng Tingting, Zhang Haoyu. Research on Flight Plan Optimization Based on Airport Delay Prediction [J]. Transportation System Engineering and Information, 2016, 16 (06): 189-195.

33. Gao qiang, Zhou Qin, Chen Xin. Redistribution of Relaxation Time for Flight Overrides Based on Affected Delays [J]. Journal of South China University of Technology, 2019, 10:151-156.

34. Zhang Haifeng, Hu Minghua. Short term flight plan scheduling model and algorithm for airlines [J]. Journal of Nanjing University of Aeronautics and Astronautics, 2015, 47 (04): 553-558.

35. Zhou Qin, Gao Qiang, Li Weiwen. Aircraft Path Stochastic Optimization Model Based on Impact Delay [J]. Traffic Information and Safety, 2017, 35 (03): 117-123.

36. Implementation Manual for Collaborative Decision Making at European Airports (Chinese Version) [S] Air Traffic Management Bureau of the Civil Aviation Administration of China, 2013.

37. Guo Yaxi. On the Development of Civil Aviation Collaborative Decision Making (CDM) System [J]. Chinese and Foreign Entrepreneurs, 2020 (04): 29-30.

38. Business - Airline and Airport Management; Data from Universidade da Beira Interior Broaden Understanding of Airline and Airport Management (The airport A-CDM operational implementation description and challenges). 2020.

39. Lu Min, Feng Xia, Xu Tao. A review of research on airport collaborative decision-making [J]. Intelligent Building, 2018 (08): 58-61.

Refbacks

  • There are currently no refbacks.


Copyright (c) 2024 LI De long, XU Hai wen, FU Qiang

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.


This site is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).