[ 1 ] The International Air Transport Association. Infographic: economics air passenger demand [Internet]. Montreal: The International Air Transport Association; 2019. Available from: https://www.iata.org/en/iata-repository/ publications/economic-reports/Infographic_Economics_Air_Passenger_Demand_ 2019/. 链接1

[ 2 ] Eltoukhy AEE, Chan FTS, Chung SH. Airline schedule planning: a review and future directions. Ind Manage Data Syst 2017;117(6):1201–43. 链接1

[ 3 ] Zhou L, Liang Z, Chou CA, Chaovalitwongse WA. Airline planning and scheduling: models and solution methodologies. Front Eng Manag 2020;7:1–26. 链接1

[ 4 ] Civil Aviation Administration of China. Statistical bulletin of civil aviation industry development in 2019. Beijing: Civil Aviation Administration of China; 2020. Chinese.

[ 5 ] OAG. Punctuality League [Internet]. Luton: OAG; 2020. Available from: https:// www.oag.com/punctuality-league-2020-report?submissionGuid=8ba7ac6c475b-4821-9456-4c8203499733. 链接1

[ 6 ] Clarke MDD. Irregular airline operations: a review of the state-of-the-practice in airline operations control centers. J Air Transp Manage 1998;4(2):67–76. 链接1

[ 7 ] Filar JA, Manyem P, White K. How airlines and airports recover from schedule perturbations: a survey. Ann Oper Res 2001;108(1–4):315–33. 链接1

[ 8 ] Kohl N, Larsen A, Larsen J, Ross A, Tiourine S. Airline disruption management— perspectives, experiences and outlook. J Air Transp Manage 2007;13 (3):149–62. 链接1

[ 9 ] Clausen J, Larsen A, Larsen J, Rezanova NJ. Disruption management in the airline industry—concepts, models and methods. Comput Oper Res 2010;37 (5):809–21. 链接1

[10] Belobaba P, Odoni A, Barnhart C, editors. The global airline industry. Hoboken: John Wiley and Sons, Ltd.; 2009.

[11] Barnhart C, Smith B, editors. Quantitative problem solving methods in the airline industry: a modeling methodology handbook. Berlin: Springer; 2012.

[12] Floudas CA, Pardalos PM, editors. Encyclopedia of optimization. 2nd ed. Berlin: Springer; 2009.

[13] Hane CA, Barnhart C, Johnson EL, Marsten RE, Nemhauser GL, Sigismondi G. The fleet assignment problem: solving a large-scale integer program. Math Program 1995;70(1–3):211–32. 链接1

[14] Yan S, Yang DH. A decision support framework for handling schedule perturbation. Transp Res Pt B Methodol 1996;30(6):405–19. 链接1

[15] Yan S, Lin CG. Airline scheduling for the temporary closure of airports. Transport Sci 1997;31(1):72–82. 链接1

[16] Andersson T, Värbrand P. The flight perturbation problem. Transp Plann Technol 2004;27(2):91–117. 链接1

[17] Bard JF, Yu G, Argüello MF. Optimizing aircraft routings in response to groundings and delays. IIE Trans 2001;33(10):931–47. 链接1

[18] Thengvall BG, Bard JF, Yu G. Balancing user preferences for aircraft schedule recovery during irregular operations. IIE Trans 2000;32(3):181–93. 链接1

[19] Thengvall BG, Yu G, Bard JF. Multiple fleet aircraft schedule recovery following hub closures. Transp Res Pt A Policy Pract 2001;35(4):289–308. 链接1

[20] Vos HWM, Santos BF, Omondi T. Aircraft schedule recovery problem—a dynamic modeling framework for daily operations. Transp Res Procedia 2015;10:931–40. 链接1

[21] Vink J, Santos BF, Verhagen WJC, Medeiros I, Filho R. Dynamic aircraft recovery problem—an operational decision support framework. Comput Oper Res 2020;117:104892. 链接1

[22] Argüello MF, Bard JF, Yu G. A grasp for aircraft routing in response to groundings and delays. J Comb Optim 1997;1(3):211–28. 链接1

[23] Rosenberger JM, Johnson EL, Nemhauser GL. Rerouting aircraft for airline recovery. Transport Sci 2003;37(4):408–21. 链接1

[24] Eggenberg N, Salani M, Bierlaire M. Constraint-specific recovery network for solving airline recovery problems. Comput Oper Res 2010;37(6):1014–26. 链接1

[25] Wu Z, Li B, Dang C, Hu F, Zhu Q, Fu B. Solving long haul airline disruption problem caused by groundings using a distributed fixed-point computational approach to integer programming. Neurocomputing 2017;269:232–55. 链接1

[26] Liang Z, Xiao F, Qian X, Zhou L, Jin X, Lu X, et al. A column generation-based heuristic for aircraft recovery problem with airport capacity constraints and maintenance flexibility. Transp Res Pt B Methodol 2018;113:70–90. 链接1

[27] Aktürk MS, Atamtürk A, Gürel S. Aircraft rescheduling with cruise speed control. Oper Res 2014;62(4):829–45. 链接1

[28] Jarrah AIZ, Yu G, Krishnamurthy N, Rakshit A. A decision support framework for airline flight cancellations and delays. Transport Sci 1993;27(3):266–80. 链接1

[29] Thengvall BG, Bard JF, Yu G. A bundle algorithm approach for the aircraft schedule recovery problem during hub closures. Transport Sci 2003;37 (4):392–407. 链接1

[30] Andersson T. Solving the flight perturbation problem with meta heuristics. J Heuristics 2006;12(1–2):37–53. 链接1

[31] Liu TK, Jeng CR, Chang YH. Disruption management of an inequality-based multi-fleet airline schedule by a multi-objective genetic algorithm. Transp Plann Technol 2008;31(6):613–39. 链接1

[32] Wei G, Yu G, Song M. Optimization model and algorithm for crew management during airline irregular operations. J Comb Optim 1997;1(3):305–21. 链接1

[33] Teodorovic´ D, Stojkovic´ G. Model to reduce airline schedule disturbances. J Transp Eng 1995;121(4):324–31. 链接1

[34] Stojkovic´ M, Soumis F, Desrosiers J. The operational airline crew scheduling problem. Transport Sci 1998;32(3):232–45. 链接1

[35] Lettovsky´ L, Johnson EL, Nemhauser GL. Airline crew recovery. Transport Sci 2000;34(4):337–48. 链接1

[36] Yu G, Argüello M, Song G, McCowan SM, White A. A new era for crew recovery at continental airlines. Interfaces 2003;33(1):5–22. 链接1

[37] Guo Y, Suhl L, Thiel MP. Solving the airline crew recovery problem by a genetic algorithm with local improvement. Oper Res 2005;5(2):241–59. 链接1

[38] Medard CP, Sawhney N. Airline crew scheduling from planning to operations. Eur J Oper Res 2007;183(3):1013–27. 链接1

[39] Stojkovic´ M, Soumis F. An optimization model for the simultaneous operational flight and pilot scheduling problem. Manage Sci 2001;47 (9):1290–305. 链接1

[40] Stojkovic´ M, Soumis F. The operational flight and multi-crew scheduling problem. Yugosl J Oper Res 2005;15(1):25–48. 链接1

[41] Abdelghany A, Ekollu G, Narasimhan R, Abdelghany K. A proactive crew recovery decision support tool for commercial airlines during irregular operations. Ann Oper Res 2004;127(1–4):309–31. 链接1

[42] Desrochers M, Soumis F. A generalized permanent labeling algorithm for the shortest path problem with time windows. Inf Syst Res 1988;26(3):191–212. 链接1

[43] Nissen R, Haase K. Duty-period-based network model for crew rescheduling in European airlines. J Sched 2006;9(3):255–78. 链接1

[44] Chang SC. A duty based approach in solving the aircrew recovery problem. J Air Transp Manage 2012;19:16–20. 链接1

[45] Bratu S, Barnhart C. Flight operations recovery: new approaches considering passenger recovery. J Sched 2006;9(3):279–98. 链接1

[46] Abdelghany KF, Abdelghany AF, Ekollu G. An integrated decision support tool for airlines schedule recovery during irregular operations. Eur J Oper Res 2008;185(2):825–48. 链接1

[47] Petersen JD, Sölveling G, Clarke JP, Johnson EL, Shebalov S. An optimization approach to airline integrated recovery. Transport Sci 2012;46(4): 482–500. 链接1

[48] Maher SJ. A novel passenger recovery approach for the integrated airline recovery problem. Comput Oper Res 2015;57:123–37. 链接1

[49] Zhang D, Henry Lau HYK, Yu C. A two stage heuristic algorithm for the integrated aircraft and crew schedule recovery problems. Comput Ind Eng 2015;87:436–53. 链接1

[50] Maher SJ. Solving the integrated airline recovery problem using column-androw generation. Transport Sci 2016;50(1):216–39. 链接1

[51] Arıkan U, Gürel S, Aktürk MS. Flight network-based approach for integrated airline recovery with cruise speed control. Transport Sci 2017;51 (4):1259–87. 链接1

[52] Arıkan U, Gürel S, Aktürk MS. Integrated aircraft and passenger recovery with cruise time controllability. Ann Oper Res 2016;236(2):295–317. 链接1

[53] Marla L, Vaaben B, Barnhart C. Integrated disruption management and flight planning to trade off delays and fuel burn. Transport Sci 2017;51(1):88–111. 链接1

[54] Jafari N, Zegordi SH. The airline perturbation problem: considering disrupted passengers. Transp Plann Technol 2010;33(2):203–20. 链接1

[55] Jafari N, Zegordi SH. Simultaneous recovery model for aircraft and passengers. J Franklin Inst 2011;348(7):1638–55. 链接1

[56] Hu Y, Xu B, Bard JF, Chi H, Gao M. Optimization of multi-fleet aircraft routing considering passenger transiting under airline disruption. Comput Ind Eng 2015;80:132–44. 链接1

[57] Bisaillon S, Cordeau JF, Laporte G, Pasin F. A large neighbourhood search heuristic for the aircraft and passenger recovery problem. 4OR-Q J Oper Res 2011;9(2):139–57. 链接1

[58] Sinclair K, Cordeau JF, Laporte G. Improvements to a large neighborhood search heuristic for an integrated aircraft and passenger recovery problem. Eur J Oper Res 2014;233(1):234–45. 链接1

[59] Sinclair K, Cordeau JF, Laporte G. A column generation post-optimization heuristic for the integrated aircraft and passenger recovery problem. Comput Oper Res 2016;65:42–52. 链接1

[60] Jozefowiez N, Mancel C, Mora-Camino F. A heuristic approach based on shortest path problems for integrated flight, aircraft, and passenger rescheduling under disruptions. J Oper Res Soc 2013;64(3):384–95. 链接1

[61] Hu Y, Song Y, Zhao K, Xu B. Integrated recovery of aircraft and passengers after airline operation disruption based on a GRASP algorithm. Transport Res E-Log 2016;87:97–112. 链接1