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Handling the pseudo pilot assignment problem in air traffic control training by using NASA TLX

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  • Dönmez, Kadir
  • Demirel, Soner
  • Özdemir, Mustafa

Abstract

Simulator courses play an important role in a department training air traffic controllers (ATCOs). One of the most important elements of these courses is a pseudo-pilot (PP) who has active tasks during simulator training. At Eskisehir Technical University (ESTU) PP assignments are made manually to meet the demand of related courses by considering the availability of PP. Even where it is attempted to assign each PP equally in terms of period, personal workloads differ due to the different psychological (mental) and physiological requirements of the simulator tasks. In this study, the PP assignment problem is investigated using mixed-integer programming (MIP). For this purpose, firstly, an equal period assignment to pilots was attempted with a mathematical model, called the Equality of Periods Model (EPM). Then, simulator tasks were weighted using the NASA Task Load Index (NASA TLX), and an Equality of Workload Model (EWLM) was created based on these weights. Finally, these models were combined to make fair assignments with the Fair Model (FM). The results indicate that the proposed models significantly reduce the differences of workload and working period compared to manual assignment (MA).

Suggested Citation

  • Dönmez, Kadir & Demirel, Soner & Özdemir, Mustafa, 2020. "Handling the pseudo pilot assignment problem in air traffic control training by using NASA TLX," Journal of Air Transport Management, Elsevier, vol. 89(C).
    • Handle: RePEc:eee:jaitra:v:89:y:2020:i:c:s0969699720305172
    DOI: 10.1016/j.jairtraman.2020.101934
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    References listed on IDEAS

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    1. Vermuyten, Hendrik & Lemmens, Stef & Marques, Inês & Beliën, Jeroen, 2016. "Developing compact course timetables with optimized student flows," European Journal of Operational Research, Elsevier, vol. 251(2), pages 651-661.
    2. De Causmaecker, Patrick & Demeester, Peter & Vanden Berghe, Greet, 2009. "A decomposed metaheuristic approach for a real-world university timetabling problem," European Journal of Operational Research, Elsevier, vol. 195(1), pages 307-318, May.
    3. Badri, Masood A., 1996. "A two-stage multiobjective scheduling model for [faculty-course-time] assignments," European Journal of Operational Research, Elsevier, vol. 94(1), pages 16-28, October.
    4. Hultberg, Tim H. & Cardoso, Domingos M., 1997. "The teacher assignment problem: A special case of the fixed charge transportation problem," European Journal of Operational Research, Elsevier, vol. 101(3), pages 463-473, September.
    5. Asratian, A. S. & de Werra, D., 2002. "A generalized class-teacher model for some timetabling problems," European Journal of Operational Research, Elsevier, vol. 143(3), pages 531-542, December.
    6. Domenech, B & Lusa, A, 2016. "A MILP model for the teacher assignment problem considering teachers’ preferences," European Journal of Operational Research, Elsevier, vol. 249(3), pages 1153-1160.
    7. Carrasco, M. P. & Pato, M. V., 2004. "A comparison of discrete and continuous neural network approaches to solve the class/teacher timetabling problem," European Journal of Operational Research, Elsevier, vol. 153(1), pages 65-79, February.
    8. Saviniec, Landir & Santos, Maristela O. & Costa, Alysson M. & Santos, Lana M.R. dos, 2020. "Pattern-based models and a cooperative parallel metaheuristic for high school timetabling problems," European Journal of Operational Research, Elsevier, vol. 280(3), pages 1064-1081.
    9. Ozdemir, Mujgan S. & Gasimov, Rafail N., 2004. "The analytic hierarchy process and multiobjective 0-1 faculty course assignment," European Journal of Operational Research, Elsevier, vol. 157(2), pages 398-408, September.
    10. Daskalaki, S. & Birbas, T. & Housos, E., 2004. "An integer programming formulation for a case study in university timetabling," European Journal of Operational Research, Elsevier, vol. 153(1), pages 117-135, February.
    11. Ioannis X. Tassopoulos & Christina A. Iliopoulou & Grigorios N. Beligiannis, 2020. "Solving the Greek school timetabling problem by a mixed integer programming model," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 71(1), pages 117-132, January.
    12. Saviniec, Landir & Santos, Maristela O. & Costa, Alysson M., 2018. "Parallel local search algorithms for high school timetabling problems," European Journal of Operational Research, Elsevier, vol. 265(1), pages 81-98.
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