Robustness as a Method of Airline Pro-Active Disruption Management
Disruptions in operations cost airlines millions of Euro every year and might also lead to passenger migration toward competing service providers or event other means of transportation. For years now operation research has been supplying airlines with dedicated disruption management tools to minimize the aftermath of a disruption and help recover from the irregular operation. Nonetheless, previous decade brought a new heading of the research studying methods of pro-active approach to disruptions known as robust planning, partly supported by the development in hardware technologies and software solutions, which enabled this concept to penetrate through the complexity of airline operations. We bring on overview of airline disruption management, the pro-active approach of robust planning as well as review of recent research on airline robustness.
Copyright © 2015 Praise Worthy Prize - All rights reserved.
Clausen, J. et al. (2010) Disruption management in the airline industry — Concepts, models and methods. Computers and Operations Research. 37 (5). p. 809-821
Teodorovic, D. (1985) A Model for Designing the Meteorological most reliable Airline Schedule. European Journal of Operational Research. 21 (2). p. 156-164.
Teodorovic, D. & Gubernic, S. (1984) Optimal dispatching strategy on an airline network after a schedule perturbation. European Journal of Operational Research. 15 (2). p. 178-182.
Teodorovic, D. & Stojkovic, G. (1990) Model for Operational Daily Airline Scheduling. Transportation Planning and Technology. 14 (4). p. 273-285.
Teodorovic, D. & Stojkovic, G. (1995) Model to Reduce Airline Schedule Disturbances. Journal of Transportation Engineering. 121 (4). p. 324-331.
Kohl, N. et al. (2007) Airline disruption management – Perspectives, experiences and outlook. Journal of Air Transport Management. 13 (3). p. 149-162.
Wieland, A. &Wallenburg, C.M. (2012) Dealing with supply chain risks: Linking risk management practices and strategies to performance. International Journal of Physical Distribution and Logistics Management. 42 (10). p. 887-905.
Lempert, R. J. & Collins, M. T. (2007) Managing the Risk of Uncertain Threshold Response: Comparison of Robust, Optimum, and Precautionary Approaches. Risk Analysis. 27 (4). p. 1009–1026.
Lan, S., Clarke, J.-P. & Barnhart, C. (2006) Planning for Robust Airline Operations Optimizing Aircraft Routings and Flight Departure Times to Minimize Passenger Disruptions. Transportation Science. 40 (1). p. 15-28.
Jin, H. (1998) Designing Robust Railroad Blocking Plans (Doctoral dissertation). Retrieved from MIT Libraries. (http://hdl.handle.net/1721.1/50477)
Lan, S. (2003) Planning for Robust Airline Operations: Optimizing Aircraft Routings and Flight Departure Times to Achieve Minimum Passenger Disruptions (Doctoral dissertation). Retrieved from MIT Libraries. (http://hdl.handle.net/1721.1/17568)
Shaefer, A. J. et al. (2005) Airline crew scheduling under uncertainty. Transportation Science. 39 (3). p. 340-348.
Yen, J. W. & Birge, J. R. (2006) A stochastic programming approach to the airline crew scheduling problem. Transportation Science. 40 (1). p. 3-14.
Gao, C., Johnson, E. L. & Smith, B. C. (2009) Integrated airline fleet and crew robust planning. Transportation Science. 43 (1). p. 2-16.
Weide, O., Ryan, D. M. & Ehrgott, M. (2010) An iterative approach to robust and integrated aircraft routing and crew scheduling. Computers and Operations Research. 37 (5). p. 833-844.
Cadarso, L. & Marín, Á. G. (2011) Integrated robust airline schedule development. Procedia - Social and Behavioral Sciences. 20. p.1041-1050.
EUROCONTROL. PERFORMANCE REVIEW COMMISSION (2004) Evaluating the true cost to airlines of one minute of airborn or ground delay. Brussels: Eurocontrol. (Final Report)
Ageeva, Y. (2000) Approaches to Incorporating Robustness into Airline Scheduling (Master Thesis). Retrieved from MIT Libraries. (http://hdl.handle.net/1721.1/37308)
Shebalov, S. & Klabjan, D. (2006) Robust airline crew pairing: Move-up crews. Transportation Science. 40 (3), p. 300-312.
Smith, B. C. & Johnson, E. L. (2006) Robust airline fleet assignment: Imposing station purity using station decomposition. Transportation Science. 40 (4), p. 494-516.
Rosenberger, J. M., Johnson, E. L. & Nemhauser, G. L. (2004) A robust fleet-assignment model with hub isolation and short cycles. Transportation Science. 38 (3), p. 357-368.
Kang, L. S. (2004) Degradable Airline Scheduling: an Approach to Improve Operational Robustness and Differentiate Service Quality (Doctoral dissertation). Retrieved from MIT Libraries. (http://hdl.handle.net/1721.1/17659)
Ball, M. et al. (2007) Chapter 1 Air Transportation: Irregular Operations and Control. Handbooks in Operations Research and Management Science. 14. p. 1-67.
Clausen, J. (2007) Disruption Management in Passenger Transportation – From Air to Tracks. Open Access Series in Informatics. 7. p. 30-47.
- There are currently no refbacks.
Please send any question about this web site to firstname.lastname@example.org
Copyright © 2005-2020 Praise Worthy Prize