Aircraft Maintenance Routing Problem – A Literature Survey
Abstract
The airline industry has shown significant growth in the last decade according to some indicators such as annual average growth in global air traffic passenger demand and growth rate in the global air transport fleet. This inevitable progress makes the airline industry challenging and forces airline companies to produce a range of solutions that increase consumer loyalty to the brand. These solutions to reduce the high costs encountered in airline operations, prevent delays in planned departure times, improve service quality, or reduce environmental impacts can be diversified according to the need. Although one can refer to past surveys, it is not sufficient to cover the rich literature of airline scheduling, especially for the last decade. This study aims to fill this gap by reviewing the airline operations related papers published between 2009 and 2019, and focus on the ones especially in the aircraft maintenance routing area which seems a promising branch.
References
Air Transport Action Group. Aviation: Benefits Beyond Borders. 2018. Available from: https://aviationbenefits.org/media/166712/abbb18_global-summary_web.pdf [Accessed 13th June 2020].
Mazareanu E. Global Air Traffic - Annual Growth of Passenger Demand 2006-2021. 2020. Available from: https://www.statista.com/statistics/193533/growth-of-global-air-traffic-passenger-demand/ [Accessed 21st June 2020].
Demir R. Aviation Industry: MRO Trends Summary Q1-2014. 2014. Available from: https://www.slideshare.net/reyyandemir/aviation-industry-and-mro-sector-trends [Accessed 21st June 2020].
Battles B. Maintenance Costs: Significant but Tricky. 2003. Available from: https://www.aviationpros.com/aircraft/maintenance-providers/mro/article/10387195/aircraft-maintenance-costs-significant-but-tricky. [Accessed 4th April 2019].
The International Air Transport Association. IATA Annual Review 2017. 2017. Available from: http://www.iata.org/publications/Documents/iata-annual-review-2017.pdf [Accessed 17th March 2018].
Chen D, Wang X, Zhao J. Aircraft maintenance decision system based on real-time condition monitoring. Procedia Engineering. 2012;29: 765-769.
Zhou G, Zhang H. The design and implementation of aircraft maintenance on-site control system. Physics Procedia. 2012;33: 528-534.
Colbacchini S, Gahafer A, McEvoy L, Park B. Simulation of the support fleet maintenance of modern stealth fighter aircraft. Proceedings of the IEEE Systems and Information Engineering Design Conference, SIEDS 2016, 29 April 2016, Virginia, USA; 2016.
Díaz-Ramírez J, Huertas JI, Trigos F. Aircraft maintenance, routing, and crew scheduling planning for airlines with a single fleet and a single maintenance and crew base. Computers & Industrial Engineering. 2014;75: 68-78.
Weide O, Ryan D, Ehrgott M. An iterative approach to robust and integrated aircraft routing and crew scheduling. Computers & Operations Research. 2010;37(5): 833-844.
Dunbar M, Froyland G, Wu C. An integrated scenario-based approach for robust aircraft routing, crew pairing and re-timing. Computers & Operations Research. 2014;45: 68-86.
Mohamed NF, et al. A heuristic and exact method: Integrated aircraft routing and crew pairing problem. Modern Applied Science. 2016;10(4): 128-136.
Parmentier A, Meunier F. Aircraft Routing and Crew Pairing: Updated Algorithms at Air France. arXiv:1706.06901. 2017.
Mohamed NF, Zainuddin ZM, Salhi S, Mohamed NA. The integrated aircraft routing and crew pairing problem: ILP based formulations. Jurnal Teknologi. 2016;78(6-5): 79-85.
Ahmed MB, Mansour FZ, Haouari M. Robust integrated maintenance aircraft routing and crew pairing. Journal of Air Transport Management. 2018;73(C): 15-31.
Lacasse-Guay E, Desaulniers G, Soumis F. Aircraft routing under different business processes. Journal of Air Transport Management. 2010;16(5): 258-263.
Papakostas N, et al. An approach to operational aircraft maintenance planning. Decision Support Systems. 2010;48(4): 604-612.
Yang Z, Yang G. Optimization of aircraft maintenance plan based on genetic algorithm. Physics Procedia. 2012;33: 580-586.
Maher SJ, Desaulniers G, Soumis F. Recoverable robust single day aircraft maintenance routing problem. Computers & Operations Research. 2014;51: 130-145.
Liang Z, et al. Robust weekly aircraft maintenance routing problem and the extension to the tail assignment problem. Transportation Research Part B: Methodological. 2015;78: 238-259.
Başdere M, Bilge Ü. Operational aircraft maintenance routing problem with remaining time consideration. European Journal of Operational Research. 2014;235(1): 315-328.
Irvine EA, Shine KP, Stringer MA. What are the implications of climate change for trans-atlantic aircraft routing and flight time? Transportation Research Part D: Transport and Environment. 2016;47: 44-53.
Gopalan R. The aircraft maintenance base location problem. European Journal of Operational Research. 2014;236(2): 634-642.
Al-Thani NA, Ahmed MB, Haouari M. A model and optimization-based heuristic for the operational aircraft maintenance routing problem. Transportation Research Part C. 2016;72: 29-44.
Safaei N, Jardine AKS. Aircraft routing with generalized maintenance constraints. Omega. 2018;80: 111-122.
Qin Y, Chan FTS, Chung SH, Qu T. Development of MILP model for integrated aircraft maintenance scheduling and multi-period parking layout planning problems. Proceedings of the 4th International Conference on Industrial Engineering and Applications, ICIEA 2017, 27-29 April 2017, Nagoya, Japan; 2017. p. 197-203.
Sarhani M, Ezzinbi O, El Afia A, Benadada Y. Particle swarm optimization with a mutation operator for solving the preventive aircraft maintenance routing problem. Proceedings of the 3rd International Conference on Logistics Operations Management, GOL 2016, 23-25 May 2016, Fez, Morocco; 2016. p. 1-6.
Eltoukhy AEE, Chan FTS, Chung SH, Qu T. Optimization model and solution method for operational aircraft maintenance routing problem. Proceedings of the World Congress on Engineering, WCE 2017, 5-7 July 2017, London, U.K.
Orhan İ, Kapanoğlu M, Karakoç TH. Concurrent aircraft routing and maintenance scheduling. Journal of Aeronautics and Space Technologies. 2011;5(1): 73-79.
Aslamiah S, et al. Integer programming model for operational aircraft maintenance routing problem with side constraints. Proceedings of the 6th IMT-GT Conference on Mathematics, Statistics and Its Applications, ICMSA 2010, Kuala Lumpur, Malaysia.
Afsar HM, Espinouse M-L, Penz B. Building flight planning for an airline company under maintenance
constraints. Journal of Quality in Maintenance Engineering. 2009;15(4): 430-443.
Kim SJ, Lim GJ, Cho J. Drone flight scheduling under uncertainty on battery duration and air temperature. Computers & Industrial Engineering. 2018;117: 291-302.
Bulbul KG, Kasımbeylı R. An augmented lagrangian relaxation based subgradient approach to aircraft maintenance routing problem. Proceedings of the 6th International Conference on Control and Optimization with Industrial Applications, COIA 2018, 11-13 July 2018, Baku, Azerbaijan.
Zhong M, Chan FTS, Chung SH. Operational aircraft routing problem: Some insights in the capacitated maintenance resources. Proceedings of the IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2018, 16-19 December 2018, Bangkok, Thailand; 2018. p. 401-405.
Afia AE, Sarhani M. Optimization of a predictive aircraft maintenance routing model using mutated constrained particle swarm optimization. In: Lincoln CW. (eds.) Contemporary approaches and strategies for applied logistics. Pennsylvania, USA: IGI Global; 2018. p. 365-381.
Zhang X. Optimization of Flight Scheduling Problem by MATLAB. 2018. Available from: https://openscholarship.wustl.edu/cgi/viewcontent.cgi?article=1000&context=mems5001 [Accessed 17th March 2021].
Eltoukhy AEE, et al. Robust aircraft maintenance routing problem using a turn-around time reduction approach. IEEE Transactions on Systems, Man, and Cybernetics: Systems. 2019;50(12): 4919-4932.
Cui R, Dong X, Lin Y. Models for aircraft maintenance routing problem with consideration of remaining time and robustness. Computers & Industrial Engineering. 2019;137: 106045.
Eltoukhya AEE, Chana FTS, Chunga SH, Niub B. A model with a solution algorithm for the operational aircraft maintenance routing problem. Computers & Industrial Engineering. 2018;120: 346-359.
Vos HM, Santos BF, Omondi T. Aircraft schedule recovery problem - A dynamic modeling framework for daily operations. Transportation Research Procedia. 2015;10: 931-940.
Zhang D, Lau HH, Yu C. A two stage heuristic algorithm for the integrated aircraft and crew schedule recovery problems. Computers & Industrial Engineering. 2015;87: 436-453.
Dožić S, Kalić M, Babić O. Heuristic approach to the airline schedule disturbances problem: Single fleet case. Procedia - Social and Behavioral Sciences. 2012;54: 1232-1241.
Liu T, Chen C, Chou J. Optimization of short-haul aircraft schedule recovery problems using a hybrid multiobjective genetic algorithm. Expert Systems with Applications. 2010;37(3): 2307-2315.
Hu Y, et al. Optimization of multi-fleet aircraft routing considering passenger transiting under airline disruption. Computers & Industrial Engineering. 2015;80: 132-144.
Jufri SA, et al. Arrival time flight scheduling in Kuala Lumpur international airport (KLIA). Journal of Transport System Engineering. 2018;5(1): 31-36.
Lin H, Wang Z. Flight scheduling for airport closure based on sequential decision. Proceedings of the 4th International Conference on Information Management, ICIM 2018, 25-27 May 2018, Oxford, UK; 2018. p. 241-245.
Akartunalı K, et al. Airline planning benchmark problems - Part I: Characterising networks and demand using limited data. Computers & Operations Research. 2013;40(3): 775-792.
Akartunalı K, et al. Airline planning benchmark problems - Part II: Passenger groups, utility and demand allocation. Computers & Operations Research. 2013;40(3): 793-804.
Burke EK, et al. A multi-objective approach for robust airline scheduling. Computers & Operations Research. 2010;37(5): 822-832.
Chen C, Yan S, Chen M. Applying lagrangian relaxation-based algorithms for airline coordinated flight scheduling problems. Computers & Industrial Engineering. 2010;59(3): 398-410.
Sun JY. Clustered airline flight scheduling: Evidence from airline deregulation in Korea. Journal of Air Transport Management. 2015;42: 85-94.
Jiang H, Barnhart C. Robust airline schedule design in a dynamic scheduling environment. Computers & Operations Research. 2013;40(3): 831-840.
Abdelghany A, Abdelghany K, Azadian F. Airline flight schedule planning under competition. Computers and Operations Research. 2017;87: 20-39.
Sandamali GGN, Su R, Zhang Y, Li Q. Flight routing and scheduling with departure uncertainties in air traffic flow management. Proceedings of the 13th IEEE International Conference on Control & Automation, ICCA 2017, 03-06 July 2017, Ohrid, Macedonia; 2017. p. 301-306.
Zhao S, Shao W, Zhu H. The intelligent decision of flights adjusting rule-based flight scheduling optimisation. Proceedings of the International Conference on Web Search and Data Mining, WSDM 2019, 11-15 February 2019, Melbourne, Australia.
Peng Y, Tang Q, Han Y. Research on the optimisation of flight landing scheduling with multi-runway. International Journal of Computing Science and Mathematics. 2018;9(6): 602-611.
Chen X, et al. Uncertainty-aware flight scheduling for airport throughput and flight delay optimization. IEEE Transactions on Aerospace and Electronic Systems. 2019;56(2): 853-862.
Wang Z, Zhang X. An approach of flight scheduling optimization meet the time conformance monitoring. Proceedings of the 13th World Congress on Intelligent Control and Automation, WCICA 2018, 4-8 July 2018, Changsha, China; 2018. p. 1647-1651.
Ahmadian N, Lim GJ, Torabbeigi M, Kim SJ. Collision-free multi-UAV flight scheduling for power network damage assessment. Proceedings of the International Conference on Unmanned Aircraft Systems, ICUAS 2019, 11-14 June 2019, Atlanta, USA; 2019. p. 794-798.
Azadeh A, et al. A hybrid meta-heuristic algorithm for optimization of crew scheduling. Applied Soft Computing. 2013;13(1): 158-164.
Deng G, Lin W. Ant colony optimization-based algorithm for airline crew scheduling problem. Expert Systems with Applications. 2011;38(5): 5787-5793.
Ionescu L, Kliewer N. Increasing flexibility of airline crew schedules. Procedia - Social and Behavioral Sciences. 2011;20: 1019-1028.
Dück V, Ionescu L, Kliewer N, Suhl L. Increasing stability of crew and aircraft schedules. Transportation Research Part C: Emerging Technologies. 2012;20(1): 47-61.
Saddoune M, Desaulniers G, Elhallaoui I, Soumis F. Integrated airline crew scheduling: A bi-dynamic constraint aggregation method using neighborhoods. European Journal of Operational Research. 2011;212(3): 445-454.
Suraweera P, Webb GI, Evans I, Wallace M. Learning crew scheduling constraints from historical schedules. Transportation Research Part C: Emerging Technologies. 2013;26: 214-232.
Bayliss C, De Maere G, Atkin JAD, Paelinck M. A simulation scenario based mixed integer programming approach to airline reserve crew scheduling under uncertainty. Annals of Operations Research. 2017;252(2): 335-363.
Kasirzadeh A, Saddoune M, Soumis F. Airline crew scheduling: Models, algorithms, and data sets. EURO Journal on Transportation and Logistics. 2017;6(2): 111-137.
Lijima Y, Nishi T. Column generation heuristics to airline crew scheduling problem for fair working time. Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, SMC2016, 9-12 October 2016, Budapest, Hungary.
Arayikanon K, Chutima P. Solving cockpit crew scheduling problem of a low-cost airline using metaheuristics. AIP Conference Proceedings. 2018;2044: 020002.
Ozdemir Y, Basligil H, Sarsenov B. A large scale integer linear programming to the daily fleet assignment problem: A case study in Turkey. Procedia - Social and Behavioral Sciences. 2012;62: 849-853.
Pilla VL, et al. A multivariate adaptive regression splines cutting plane approach for solving a two-stage stochastic programming fleet assignment model. European Journal of Operational Research. 2012;216(1): 162-171.
Kang Z, Ying Y, Weijie W. A dynamic flight stringbased ant colony algorithm for fleet assignment. Proceedings of the IEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2016, 20-22 May 2016, Chongqing, China; 2016. p. 302-306.
Yang Z, et al. An improved ant colony algorithm for mapreduce-based fleet assignment problem. Proceedings of the 2nd Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2017, 25-26 March 2017, Chongqing, China; 2017. p. 104-108.
Ma Q, Song H, Zhu W. Low-carbon airline fleet assignment: A compromise approach. Journal of Air Transport Management. 2018;68: 86-102.
Raudasoja L. How to include ancillaries in fleet assignment optimization: Case Finnair. Bachelor thesis. Aalto University; 2018.
Boudia M, Delahaye T, Gabteni S, Acuna-Agost R. Novel approach to deal with demand volatility on fleet assignment models. Journal of the Operational Research Society. 2017;69(6): 895-904.
Liu M, Liang B, Zheng F, Chu F. Stochastic airline fleet assignment with risk aversion. Transactions on Intelligent Transportation Systems. 2019;20(8): 3081-3090.
Dozic S, Jelovic A, Kalic M, Cangalovic M. Variable neighborhood search to solve an airline fleet sizing and fleet assignment problem. Transportation Research Procedia. 2019;37: 258-265.
Okafor EG, et al. Study of fleet assignment problem using a hybrid technique based on Monte Carlo simulation and genetic algorithm. Nigerian Journal of Technology. 2019;38(3): 756-762.
Anzoom R, Hasin MAA. Optimal fleet assignment using ant colony algorithm. Proceedings of the International Conference on Production and Operations Management Society, POMS 2018, 14-16 December 2018, Peradeniya, Sri Lanka; 2018. p. 1-6.
Silva M, Poss M. Distributionally Robust airline fleet assignment problem. Proceedings of the International Network Optimization Conference, INOC 2019, 12-14 June 2019, Avignon, France.
Su AJ, Yang WD, Zhang C, Kong MX. 2019. Robust Modeling for Fleet Assignment Problem Based on GASVR Forecast. Journal of Physics: Conf. Series 1187. DOI: 10.1088/1742-6596/1187/4/042062
Dahel N-E. A fleet assignment model for optimizing military airlift. Proceedings of the 47th Annual Meeting of Western Decision Sciences Institute, WDSI 2018, 3-6 April 2018, USA.
Bruecker PD, Bergh JV, Beliën J, Demeulemeester E. A model enhancement heuristic for building robust aircraft maintenance personnel rosters with stochastic constraints. European Journal of Operational Research. 2015;246(2): 661-673.
Qiang F, Songjie L, Bo S. A multi-agent based intelligent configuration method for aircraft fleet maintenance personnel. Chinese Journal of Aeronautics. 2014;27(2): 280-290.
Mackenzie A, Miller J, Hill RR, Chambal SP. Application of agent based modelling to aircraft maintenance manning and sortie generation. Simulation Modelling Practice and Theory. 2012;20(1): 89-98.
Datta PP, Srivastava A, Roy R. A simulation study on maintainer resource utilization of a fast jet aircraft maintenance line under availability contract. Computers in Industry. 2013;64(5): 543-555.
Gürkan H, Gürel S, Aktürk MS. An integrated approach for airline scheduling, aircraft fleeting and routing with cruise speed control. Transportation Research Part C: Emerging Technologies. 2016;68: 38-57.
Dong Z, Chuhang Y, Lau HH. An integrated flight scheduling and fleet assignment method based on a discrete choice model. Computers & Industrial Engineering. 2016;98: 195-210.
Cadarso L, Marín Á. Robust passenger oriented timetable and fleet assignment integration in airline planning. Journal of Air Transport Management. 2013;26: 44-49.
Pita JP, Adler N, Antunes AP. Socially oriented flight scheduling and fleet assignment model with an application to Norway. Transportation Research Part B: Methodological. 2014;61: 17-32.
Cadarsoa L, Marín Á. Integrated robust airline schedule development. Procedia - Social and Behavioral Sciences. 2011;20: 1041-1050.
Kenan N, Jabali A, Diabat A. An integrated flight scheduling and fleet assignment problem under uncertainty. Computers & Operations Research. 2018;100: 333-342.
Mezentsev Y, Estraykh I. An optimal fleet assignment and flight scheduling problem for an airline company. Proceedings of the Russian Higher School Academy of Sciences; 2018. p. 74-90.
Tsagkas V, Nathanael D, Marmaras N. A pragmatic mapping of factors behind deviating acts in aircraft maintenance. Reliability Engineering & System Safety. 2014;130: 106-114.
Gerede E. A qualitative study on the exploration of challenges to the implementation of the safety management system in aircraft maintenance organizations in Turkey. Journal of Air Transport Management. 2015;47: 230-240.
Gerede E. A study of challenges to the success of the safety management system in aircraft maintenance organizations in Turkey. Safety Science. 2015;73: 106-116.
Chang Y, Wang Y. Significant human risk factors in aircraft maintenance technicians. Safety Science. 2010;48(1): 54-62.
Atak A, Kingma S. Safety culture in an aircraft maintenance organisation: A view from the inside. Safety Science. 2011;49(2): 268-278.
Quinlan M, Hampson I, Gregson S. Outsourcing and offshoring aircraft maintenance in the US: Implications for safety. Safety Science. 2013;57: 283-292.
Passenier D, Mols C, Bim J, Sharpanskykh A. Modeling safety culture as a socially emergent phenomenon: A case study in aircraft maintenance. Computational and Mathematical Organization Theory. 2016;22(4): 487-520.
Murça MC, Müller C. Control-based optimization approach for aircraft scheduling in a terminal area with alternative arrival routes. Transportation Research Part E: Logistics and Transportation Review. 2015;73: 96-113.
Samà M, D’Ariano A, D’Ariano P, Pacciarelli D. Optimal aircraft scheduling and routing at a terminal control area during disturbances. Transportation Research Part C: Emerging Technologies. 2014;47: 61-85.
Samà M, D’Ariano A, Pacciarelli D. Rolling horizon approach for aircraft scheduling in the terminal control area of busy airports. Transportation Research Part E: Logistics and Transportation Review. 2013;60: 140-155.
Shanmugam A, Robert TP. Ranking of aircraft maintenance organization based on human factor performance. Computers & Industrial Engineering. 2015;88: 410-416.
Yadav DK. Licensing and recognition of the aircraft maintenance engineers - A comparative study. Journal of Air Transport Management. 2010;16(5): 272-278.
Kasava NK, Yusof NM, Khademi A, Saman MZ. Sustainable domain value stream mapping (SdVSM) framework application in aircraft maintenance: A case study. Procedia CIRP. 2015;26: 418-423.
Mofokeng TJ, Marnewick A. Factors contributing to delays regarding aircraft during A-check maintenance. Proceedings of the IEEE Technology & Engineering Management Conference, TEMSCON 2017, 08-10 June 2017, Santa Clara, USA. 2017. p. 185-190.
Noweir MH, Zytoon MA. Occupational exposure to noise and hearing thresholds among civilian aircraft maintenance workers. International Journal of Industrial Ergonomics. 2013;43(6): 495-502.
Irwin E, Streilein K. Use of field-based motion capture to augment observational data in ergonomic assessment of aircraft maintenance. Procedia Manufacturing. 2015;3: 4501-4508.
Babic O, Kalic M, Babic D, Dozic S. The airline schedule optimization model: Validation and sensitivity analysis. Procedia - Social and Behavioral Sciences. 2011;20: 1029-1040.
Sandamali GGN, Su R, Zhang Y. Flight routing and scheduling under departure and en route speed uncertainty. IEEE Transactions on Intelligent Transportation Systems. 2019;21(5): 1915-1928.
Lindner M, Rosenow J, Förster S, Fricke H. Potential of integrated flight scheduling and rotation planning considering aerodynamic-, engine- and mass-related aircraft deterioration. CEAS Aeronautical Journal. 2019;10: 755-770.
Jamili A. A robust mathematical model and heuristic algorithms for integrated aircraft routing and scheduling with consideration of fleet assignment problem. Journal of Air Transport Management. 2017;58: 21-30.
Liu W-M, Zhu X-H, Qi Y-L. Integrated fleet assignment and aircraft routing based on delay propagation. Sadhana. 2016;41(7): 713-719.
Özener OÖ, et al. Solving a large-scale integrated fleet assignment and crew pairing problem. Annals of Operations Research. 2017;253(1): 477-500.
Komijan AR, Tavakkoli-Moghaddam R, Dalil SA. A mathematical model for an integrated airline fleet assignment and crew scheduling problem solved by vibration damping optimization. Scientica Iranica. 2019.
Abdelrahman EEE. Optimizing aircraft routing of airline and maintenance staffing of maintenance providers using game theoretic model. PhD thesis. The Hong Kong Polytechnic University; 2018.
Chan FTS, Eltoukhy AEE. Investigating the interrelationship between stochastic aircraft routing of airlines and maintenance staffing of maintenance providers. Proceedings of the 5th International Conference on Industrial Engineering and Applications, ICIEA 2018, 26-28 April 2018, Singapore, Singapore. 2018. p. 254-261.
Eltoukhya AEE, Wangb ZX, Chana FTS, Fuc X. Data analytics in managing aircraft routing and maintenance staffing with price competition by a stackelberg-nash game model. Transportation Research Part E. 2019;122(C): 143-168.
Eltoukhya AEE, Wangb ZX, Chana FTS, Chunga SH. Joint optimization using a leader–follower stackelberg game for coordinated configuration of stochastic operational aircraft maintenance routing and maintenance staffing. Computers & Industrial Engineering. 2018;125: 46-68.
Safaei N. Combined Aircraft Maintenance Routing and Maintenance Task Scheduling. 2016. Available from: https://patentimages.storage.googleapis.com/1f/d8/84/375070a1f0e7ea/WO2016157099A1.pdf [Accessed 25th August 2020].
Smith BC, Leimkuhler JF, Darrow RM. Yield management at American Airlines. Interfaces. 1992;22(1): 8-32.
Subramanian R, et al. Coldstart: Fleet assignment at Delta Air Lines. Interfaces. 1994;24(1): 104-120.
Van den Bergh J, de Bruecker P, Beliën J, Peeters J. Aircraft maintenance operations: State of art. Faculty of Economics and Business, HUBrussel. Report number: 2013/09, 2013.
Eltoukhy AEE, Chan FTS, Chung SH. Airline schedule planning: A review and future directions. Industrial Management & Data Systems. 2017;117(6): 1201-1243.
Stoller G. USA Today: Planes with Maintenance Problems Flown Anyway. 2010. Available from: https://forums.jetcareers.com/threads/usa-today-planes-with-maintenance-problems-flown-anyway.102981/ [Accessed 17th March 2018].
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