Cascading Delay Risk of Airline Workforce Deployments with Crew Pairing and Schedule Optimization

Risk Analysis

Volumn 37, Issue 8, 2017, Pages 1443-1458

  Chung, Sai Ho ^a   Ma, Hoi Lam ^a   Chan, Hing Kai ^b  

^a HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

^b University of Nottingham   (China)

Author keywords

Big data; flight reliability; robust crew pairing

Indexed keywords

AIR TRANSPORTATION; FORECASTING; NEURAL NETWORKS;

CASCADE NEURAL NETWORKS; CREW PAIRING; FLIGHT RELIABILITIES; FLIGHT SCHEDULES; LEARNING ABILITIES; NUMERICAL EXPERIMENTS; PREDICTION ACCURACY; SCHEDULE OPTIMIZATIONS;

BIG DATA;

AIRLINE INDUSTRY; AIRPORT; ARRIVAL TIME; ARTIFICIAL NEURAL NETWORK; DATA SET; LEARNING; NUMERICAL METHOD; OPTIMIZATION; RESEARCH WORK; RISK ASSESSMENT;

EID: 85006733656     PISSN: 02724332     EISSN: 15396924     Source Type: Journal    
DOI: 10.1111/risa.12746     Document Type: Article

References (43)

1. Wu WY, Liao WY. A balanced scorecard envelopment approach to assess airlines’ performance. Industrial Management & Data Systems, 2014; 114(1):123–143.
2. IATA, Air Passenger Market Analysis, September 2015.
3. Shafieezadeh A, Cha E, Ellingwood BR. A decision framework for managing risk to airports from terrorist attack. Risk Analysis, 2015; 35(2):292–306.
4. Stewart MG, Mueller J. Terrorism risks and cost-benefit analysis of aviation security. Risk Analysis, 2013; 33(5):893–908.
5. Wang Y, Andoh-Baidoo FK, Sun J. Security investment in aviation industry: A longitudinal analysis, 2014; 114(2):276–291.
6. Ayra ES, Insua DR, Castellanos ME, Larbi L. Risk analysis for unintentional slide deployment during airline operations. Risk Analysis, 2015; 35(9):1652–1662.
7. Dunbar M, Froyland G, Wu CL. Robust airline schedule planning: Minimizing propagated delay in an integrated routing and crewing framework. Transportation Science, 2012; 46(2):204–216.
8. Rogerson EC, Lamber JH. Prioritizing risk via several expert perspectives with application to airport runway safety. Reliability Engineering and System Safety, 2012; 103:22–34.
9. Rogerson EC, Lambert JH, Johns AF. Runway safety program evaluation with uncertainties of benefits and costs. Journal of Risk Research, 2013; 16(5):523–539.
10. Liau BY, Tan PP. Gaining customer knowledge in low cost airlines through text mining. Industrial Management & Data Systems, 2014; 114(9):1344–1359.
11. Teng KY, Thekdi SA, Lambert JH. Risk and safety program performance evaluation and business process modeling. IEEE Transactions on Systems, Man, and Cybernetics: Part A, 2012; 42(6):1504–1513.
12. Teng KY, Thekdi SA, Lambert JH. Identification and evaluation of priorities in the business process of a risk or safety organization. Reliability Engineering and System Safety. 2011; 99:74–86.
13. Parlak AI, Lambert JH, Guterbock TM, Clements JL. Population behavioral scenarios influencing radiological disaster preparedness and planning. Accident Analysis and Prevention, 2012; 48:353–362.
14. Lambert JH, Parlak AI, Zhou Q, Miller JS, Fontaine MD, Gutterbock TM, Clements JL, Thekdi, SA. Understanding and managing disaster evacuation on a transportation network. Accident Analysis and Prevention, 2012; 50(1):645–659.
15. Ball M, Barnhart C, Dresner M, Hansen M, Neels K, Odoni A, Peterson E, Sherry L, Trani A, Zou B. Total Delay Impact Study. The National Center of Excellence for Aviation Operation Research, NEXTOR, Final Report, 2010.
16. Inniss T, Ball MO. Estimating one-parameter airport arrival capacity distributions for air traffic flow management. Air Traffic Control Quarterly. 2004; 12:223–252.
17. Tu Y, Ball MO, Jank WS. Estimating flight departure delay distributions—A statistical approach with long-term trend and short-term pattern. Journal of American Statistical Association, 2008; 103(481):112–125.
18. Papakostas N, Papachatzakis P, Xanthakis V, Mourtzis D, Chryssolouris G. An approach to operational aircraft maintenance planning. Decision Support Systems, 2010; 48:604–612.
19. Ionescu L, Gwiggner C, Kliewer N. Data analysis of delays in airline networks. Business & Information Systems Engineering, 2010; 58(2):119–133.
20. Rebollo JJ, Balakrishnan H. Characterization and prediction of air traffic delays. Transportation Research Part C, 2014; 44:231–241.
21. Mercier A, Cordeau JF, Soumis F. A computational study of benders decomposition for the integrated aircraft routing and crew scheduling problem. Computers & Operations Research, 2005;32:1451–1476.
22. Shebalov S, Klabjan D. Robust airline crew pairing: Move-up crews. Transportation Science, 2006; 40(3):300–312.
23. Muter İ, Birbil I, Bülbül K, Şahin G, Yenigün H, Taş D, Tüzün D. Solving a robust airline crew pairing problem with column generation. Computers & Operations Research, 2013; 40(3):815–830.
24. Chandran BG. Predicting Airspace Congestion Using Approximate Queueing Models. Masters Thesis, University of Maryland, College Park.
25. Schaefer AJ, Johnson EL, Kleywegt AJ, Nemhauser GL. Airline crew scheduling under uncertainty. Transportation Science, 2005; 39:340–348.
26. Ahmadbeygi S, Cohn A, Lapp M. Decreasing airline delay propagation by re-allocating scheduled slack. IIE Transactions, 2010; 42:478–489.
27. Sohoni MG, Johnson EL, Bailey TG. Operational airline reserve crew planning. Journal of Scheduling, 2006; 9(3):203–221.
28. Dück V, Lonescu L, Liewer N, Suhl L. Increasing stability of crew and aircraft schedules. Transportation Research C, 2012; 20:47–61.
29. Anbil R, Gelman E, Patty B, Tanga R. Recent advances in crew-pairing optimization at American airlines. Interfaces, 1991; 21(1):62–74.
30. Yan S, Chang JC. Airline cockpit crew scheduling. European Journal of Operational Research, 2002; 136:501–511.
31. Saddoune M, Desaulniers G, Elhallaoui I, Soumis F. Integrated airline crew pairing and crew assignment by dynamic constraint aggregation. Transportation Science, 2012; 46(1):39–55.
32. Barnhart C, Hatay L, Johnson EL. Deadhead selection for the long-haul crew pairing problem. Operations Research, 1995; 43(3):491–499.
33. Klabjan D, Johnson EL, Nemhauser G, Gelman E, Ramaswamy S. Solving large airline crew scheduling problems: Random pairing generation and strong branching. Computational Optimization and Applications, 2001; 20:73–91.
34. Zhu X, Wilhelm WE. A three-stage approach for resource-constrained shortest path as a sub-problem in column generation. Computers & Operations Research, 2012; 39:164–178.
35. Saddoune M, Desauliners G, Soumis F. Aircrew pairings with possible repetitions of the same flight number. Computers & Operations Research, 2013; 40:805–814.
36. Desaulniers G, Desrosiers J, Dumas Y, Marc S, Rioux B, Solomon MM. Crew pairing in Air France. European Journal of Operational Research, 1997; 97:245–259.
37. Lavoie S, Minoux M, Odier E. A new approach for crew pairing problems by column generation with an application to air transportation. European Journal of Operational Research, 1988; 35:45–58.
38. Barnhart C, Johnson EL, Nemhauser GL, Vance PH. Crew scheduling. Pp. 493–521 in Hall, R (ed.), Handbook of Transportation Science. Norwell: Kluwer Academic Publisher, 1999.
39. Cacchiani V, Salazar-González JJ. Optimal solutions to a real-world integrated airline scheduling problem. Transportation Science, 2016; in press.
40. http://weather.org/weatherorg_records_and_averages.htm.
41. Sridhar B, Wang Y, Klein A. Modeling flight delays and cancellations at the national, regional and airport levels in the United States. Eighth USA/Europe Air Traffic Management Research and Development Seminar, 2009.
42. Hussain S, Mokhtar M, Howe JM. Sensor failure detection, identification, and accommodation using fully connected cascade neural network. IEEE Transactions on Industrial Electronics, 2015; 62(3):1683–1692.
43. Irnich S, Desaulniers G. Shortest path problems with resource constraints. Pp. 33–35 in Desaulniers G, Desrosiers J, Solomon MM (eds). Column Generation. New York: Springer, 2005.