空勤組員疲勞管理為國際之趨勢，台灣民用航空局於民國106年2月3日參酌美國聯邦航空法規FAR第117編，預告修正《航空器飛航作業管理規則部分條文草案》，以修訂民用航空運輸業之飛航組員及客艙組員之飛航時限及休息期間等規範，然修正草案較現行法規標準為高，對航空公司之營運造成極大影響。如我國未來為符合國際飛航標準及管理、改善空勤組員之疲勞風險管理，將參酌國際標準，則有必要探討國際標準對我國航空公司營運之影響程度。本研究以飛航國際航線之客艙組員為討論目標，藉由訪談、班表資料蒐集及航網分析以建構組員之勤務組合排班模型，並參酌歐盟規範REGULATION (EU) No.83/2014及美國聯邦航空法規FAR第117編設定情境限制標準，並納入航空公司裕度設定及勞基法限制進行敏感度分析，以求得各情境限度對區域航線及長程航線之派遣影響，及對台灣民航產業之影響因子。
依據分析結果，針對區域航線，勞基法為主要影響因素，因此在加入勞基法之工作時間限制下，民航法之標準(AOR、EASA及FAA)失其效用，並不會影響派遣結果，而長程航線由於機上休息設備之要求增加及時限縮減，限縮航空公司派遣彈性，另由於法規休息限制及累計規範，影響班表安排及有額外人力需求，因此為降低對航空公司之衝擊，建議考量時限的訂定，或在逐步縮減的同時給予營運彈性，另為使訂定之民航標準發揮疲勞風險管理之效果，建議考慮對勞基法工時限制之鬆綁。

Aircrew fatigue management is an international trend. On February 3, 2017, Taiwan Civil Aviation Administration announced the revision of the "Draft Provisions of Aircraft Flight Operations Regulations", which considered Federal Aviation Regulation Part117. The draft amendment is higher than the current regulatory standards, which has a great impact on airlines. The study establishes regulatory sensitivity analysis in consideration of EASA regulations and FAR Part 117 to obtain the impact of each situational limit on regional and long-haul routes. In addition, by way of case study, to discuss the operational impact of long-term service arrangements and personnel requirements under various regulations.
According to the results, for regional routes, Labor Standard Act is the main factor, and the standard of civil aviation law is ineffective and will not affect the results of duties. For long-haul routes, due to the increased requirements for in-flight rest equipment and time limit reduction, limited the flexibility of airline operation. Rest restrictions and cumulative standards affect schedule arrangements and require additional manpower needs. To reduce the impact for airlines, it should be full considering the setting of time limits or giving operational flexibility while gradually reducing the limits. On the other hand, for the established civil aviation standards to exert the effects of fatigue risk management, consideration should be given to the relaxation of the working hours restrictions of Labor Standards Act.

英文文獻
AhmadBeygi, S., Cohn, A., & Weir, M. (2009). An integer programming approach to generating airline crew pairings. Computers & Operations Research, 36(4), 1284-1298.
Barnhart, C., Cohn, A. M., Johnson, E. L., Klabjan, D., Nemhauser, G. L., & Vance, P. H. (2003). Airline crew scheduling. In Handbook of transportation science (pp. 517-560). Springer, Boston, MA.
Brailsford, S. C., Potts, C. N., & Smith, B. M. (1999). Constraint satisfaction problems: Algorithms and applications. European Journal of Operational Research, 119(3), 557-581.
Campbell, K. W., Durfee, R. B., & Hines, G. S. (1997). FedEx generates bid lines using simulated annealing. Interfaces, 27(2), 1-16.
Dantzig, G. B., & Wolfe, P. (1961). The decomposition algorithm for linear programs. Econometrica: Journal of the Econometric Society, 767-778.
Deveci, M., & Demirel, N. C. (2016). A hybrid genetic algorithm for airline crew pairing optimization. Economic and Social Development: Book of Proceedings, 118.
Deveci, M., & Demirel, N. C. (2018). A survey of the literature on airline crew scheduling. Engineering Applications of Artificial Intelligence, 74, 54-69.
Doi, T., Nishi, T., & Voß, S. (2018). Two-level decomposition-based matheuristic for airline crew rostering problems with fair working time. European Journal of Operational Research, 267(2), 428-438.
European Aviation Safety Agency, (2014). Commission Regulation (EU) No 83/2014 on Air Operations
Flight And Duty Limitations And Rest Requirements: Flightcrew Members, 14 C.F.R. §117 (2014)
Gabriel Crainic, T., & Rousseau, J. M. (1987). The column generation principle and the airline crew scheduling problem. INFOR: Information Systems and Operational Research, 25(2), 136-151.
Gamache, M., Soumis, F., Villeneuve, D., Desrosiers, J., & Gelinas, E. (1998). The preferential bidding system at Air Canada. Transportation Science, 32(3), 246-255.
Gamache, M., Soumis, F., Marquis, G., & Desrosiers, J. (1999). A column generation approach for large-scale aircrew rostering problems. Operations research, 47(2), 247-263.
Gopalakrishnan, B., & Johnson, E. L. (2005). Airline crew scheduling: state-of-the-art. Annals of Operations Research, 140(1), 305-337.
Hiller, F.S. and Lieberman, G. J. (2015). Introduction to Operations Research, 11th.
Hoffman, K. L., & Padberg, M. (1993). Solving airline crew scheduling problems by branch-and-cut. Management science, 39(6), 657-682.
International civil aviation authority. (2016). Doc 9966 Manual for the Oversight of Fatigue Management Approaches.
International civil aviation authority. (2018). ANNEX6, Operation of Aircraft: Part Ⅰ- International Commercial Air Transport – Aeroplanes, eleven edition.
Kohl, N., & Karisch, S. E. (2004). Airline crew rostering: Problem types, modeling, and optimization. Annals of Operations Research, 127(1-4), 223-257.
Levine, D. (1996). Application of a hybrid genetic algorithm to airline crew scheduling. Computers & Operations Research, 23(6), 547-558.
Nissen, R., & Haase, K. (2006). Duty-period-based network model for crew rescheduling in European airlines. Journal of Scheduling, 9(3), 255-278.
Thiel, M. P. (2005). Team-oriented airline crew scheduling and rostering: problem description, solution approaches, and decision support. Paderborn University, Paderborn, D. Sc. Thesis.
Vance, P. H., Barnhart, C., Johnson, E. L., & Nemhauser, G. L. (1997). Airline crew scheduling: A new formulation and decomposition algorithm. Operations Research, 45(2), 188-200.
Vera Valdes, V. A. (2010). Integrating crew scheduling and rostering problems (Doctoral dissertation, alma).
Xu, N., Zhao, M., Liu, Y., & Yang, F. (2018, December). A Column Generation Based Algorithm for Airline Cabin Crew Rostering Problem. In 2018 IEEE 4th International Conference on Computer and Communications (ICCC) (pp. 2511-2515). IEEE.
Yan, S., & Tu, Y. P. (2002). A network model for airline cabin crew scheduling. European Journal of Operational Research, 140(3), 531-540.
Ye, X. (2007). Airlines’ Crew Pairing Optimization: A Brief Review. John Hopkins University.
Yildiz, B. C., Gzara, F., & Elhedhli, S. (2017). Airline crew pairing with fatigue: Modeling and analysis. Transportation Research Part C: Emerging Technologies, 74, 99-112.

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