Solving Airlines Disruption by Considering Aircraft and Crew Recovery Simultaneously

doi:10.1007/s12204-013-1389-y

Abstract

Abstract: When disruptions occur, the airlines have to recover from the disrupted schedule. The recovery usually consists of aircraft recovery, crew recovery and passengers’ recovery. This paper focuses on the integrated recovery, which means above-mentioned two or more recoveries are considered as a whole. Taking the minimization of the total cost of assignment, cancellation and delay as an objective, we present a more practical model, in which the maintenance and the union regulations are considered. Then we present a so-called iterative tree growing with node combination method. By aggregating nodes, the possibility of routings is greatly simplified, and the computation time is greatly decreased. By adjusting the consolidating range, the computation time can be controlled in a reasonable time. Finally, we use data from a main Chinese airline to test the algorithm. The experimental results show that this method could be used in the integrated recovery problem.

Key words: aircraft recovery| crew recovery| integrated recovery| airlines optimal recovery

摘要： When disruptions occur, the airlines have to recover from the disrupted schedule. The recovery usually consists of aircraft recovery, crew recovery and passengers’ recovery. This paper focuses on the integrated recovery, which means above-mentioned two or more recoveries are considered as a whole. Taking the minimization of the total cost of assignment, cancellation and delay as an objective, we present a more practical model, in which the maintenance and the union regulations are considered. Then we present a so-called iterative tree growing with node combination method. By aggregating nodes, the possibility of routings is greatly simplified, and the computation time is greatly decreased. By adjusting the consolidating range, the computation time can be controlled in a reasonable time. Finally, we use data from a main Chinese airline to test the algorithm. The experimental results show that this method could be used in the integrated recovery problem.

关键词: aircraft recovery| crew recovery| integrated recovery| airlines optimal recovery

CLC Number:

N 945.15

LE Mei-long* (乐美龙), WU Cong-cong (吴聪聪). Solving Airlines Disruption by Considering Aircraft and Crew Recovery Simultaneously[J]. Journal of shanghai Jiaotong University (Science), 2013, 18(2): 243-252.

References

[1] Teodorovic D, Guberinic S. Optimal dispatching strategy on an airline network after a schedule perturbation [J]. European Journal of Operations Research, 1984, 15(2): 178-182.
[2] Yan S, Yang D H. A decision support framework for handling schedule perturbations [J]. Transportation Research B, 1996, 30(6): 405-419.
[3] Arguello M F, Bard J F, Yu G. A GRASP for aircraft routing in response to groundings and delays [J]. Journal of Combinatorial Optimization, 1997, 5: 211-228.
[4] Bard J F, Yu G, Arguello M F. Optimizing aircraft routings in response to groundings and delays [J]. IIE Transactions, 2001, 33(10): 931-947.
[5] Rosenberger J M, Johnson E L, Nemhauser G L. Rerouting aircraft for airline recovery [J]. Transportation Science, 2003, 37(4): 408-421.
[6] Eggenberg N, Salani M, Bierlaire M. A column generation algorithm for disrupted airline schedules [R]. Lausanne, Switzerland: Ecole Polytechnique Federale de Lausanne, 2007.
[7] Bazargan M. Airline operations and scheduling [M]. Farnham, England: Ashgate Publishing Limited, 2010.
[8] Wei G, Yu G, Song M. Optimization model and algorithm for crew management during airline irregular operations [J]. Journal of Combinatorial Optimization, 1997, 1: 305-321.
[9] Lettovsk′y L, Johnson E L, Nemhauser G L. Airline crew recovery [J]. Transportation Science, 2000, 34(4), 337-348.
[10] Yu G, Arguello M, Song G, et al. A new era for crew recovery at continental airlines [J]. Interfaces, 2003, 33(1): 5-22.
[11] Medard C P, Sawhney N. Airline crew scheduling from planning to operation [J]. European Journal of Operational Research, 2007, 183: 1013-1027.
[12] Abdelghany K F, Abdelghany A F, Ekollu G. An integrated decision support tool for airlines schedule recovery during irregular operations [J]. European Journal of Operational Research, 2008, 185: 825-848.
[13] Jafari N, Zegordi S H. The airline perturbation problem: Considering disrupted passengers [J]. Transportation Planning and Technology, 2010, 33(2), 203-220.
[14] Jafari N, Zegordi S H. Simultaneous recovery model for aircraft and passengers [J]. Journal of the Franklin Institute, 2010(3): 1-18.
[15] Eggenberg N, Salani M, Bierlaire M. Constraintspecific recovery network for solving airline recovery problems [J]. Computers & Operations Research, 2010, 37: 1014-1026.
[16] Petersen J D, Solveling G, Johnson E L, et al.An optimization approach to airline integrated recovery [J]. Transportation Science, 2012, 46(4): 482-500.
[17] Zhu Jin-fu. Airline transportation plan [M]. Xi’an: Northwestern Polytechnical University Press, 2010 (in Chinese).