Method of evaluation of military helicopter pilot selection criteria: a novel Grey SWARA approach
Abstract
Helicopter is a very important defence and attack tool for a country’s armed forces (army) (air force). With the rapid progress of technology, the designs of helicopters, the hardware and software elements in the helicopter have also been renewed and developed in parallel with advanced technology. Therefore, it is expected that the pilots who will use helicopters, which are an important flight tool of armed forces, will also have the qualifications to provide the necessary knowledge, skills, and criteria. The aim of the study is to determine the military helicopter pilot selection criteria and to find the importance levels of these criteria. For this purpose, three main criteria as “Health”, “Psychomotor” and “Education and Training” and thirteen sub-criteria were determined. The weights of the determined criteria were found by the Grey SWARA method, which is a current multi criteria decision making tool. According to the results of the analysis, it is found that the most important sub-criteria was “Practical Training”, while the lowest important criteria was the “Height and weight limits” criterion. With this study, the weights of the military helicopter pilot selection criteria were found for the first time with the Grey SWARA method.
Keyword : military aviation, helicopter pilot, military pilot, pilot selection, personnel selection, grey SWARA, multi criteria decision making
How to Cite
Kurnaz, S., Özdağoğlu, A., & Keleş, M. K. (2023). Method of evaluation of military helicopter pilot selection criteria: a novel Grey SWARA approach. Aviation, 27(1), 27–35. https://doi.org/10.3846/aviation.2023.18596
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Özdağoğlu, A., & Keleş, M. K. (2019). The evaluation of BIST industrial enterprises from the viewpoint of banks – SWARA-GRA integrated approach. Suleyman Demirel University Visionary Journal, 10(24), 229–241. https://doi.org/10.21076/vizyoner.532727
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Ree, M. J., & Carretta, T. R. (1996). Central role of g in military pilot selection. The International Journal of Aviation Psychology, 6(2), 111–123. https://doi.org/10.1207/s15327108ijap0602_1
Siem, F. M. (1992). Predictive validity of an automated personality inventory for air force pilot selection. The International Journal of Aviation Psychology, 2(4), 261–270. https://doi.org/10.1207/s15327108ijap0204_2
Supçiller, A. A., & Bayramoğlu, S. (2020). Wind farm location selection with interval grey numbers based I-GRA and grey EDAS methods. Journal of the Faculty of Engineering and Architecture of Gazi University, 35(4), 1847–1860. https://doi.org/10.17341/gazimmfd.609518
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Ulutaş, A., & Karaköy, Ç. (2020). Evaluation of LPI values of transition economies countries with a grey MCDM model. In Handbook of research on applied AI for international business and marketing applications (Chapter 24, pp. 499–511). IGI Global. https://doi.org/10.4018/978-1-7998-5077-9.ch024
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Yazgan, E., & Erol, D. (2016). Determination of selection criteria for civil pilot candidates. Niğde University Journal of Engineering Sciences, 5(2), 97–104. https://doi.org/10.28948/ngumuh.294659
Ağaşcıoğlu, M. A. (2011). Hava Araçlarının Optimum Kullanımında Pilot Seçme Sistemlerinin (PSS) Etkinliğinin Analizi: Bir Model Önerisi [Unpublished master dissertation, Gazi University]. Ankara, Turkey.
Bartram, D. (1987). The development of an automated testing system for pilot selection: The MICROPAT Project1. Applied Psychology, 36(3–4), 279–298. https://doi.org/10.1111/j.1464-0597.1987.tb01192.x
Çakır, E. (2017). Selecting contractor company in urban transformation using SWARA – Gray relationship analysis method. The Journal of International Scientific Researches, 2(6), 177–200. https://doi.org/10.23834/isrjournal.327313
Cao, Q., Esangbedo, M. O., Bai, S., & Esangbedo, C. O. (2019). Grey SWARA-FUCOM weighting method for contractor selection MCDM problem: A case study of floating solar panel energy system installation. Energies, 12(13), 2481. https://doi.org/10.3390/en12132481
Carretta, T. R., & Ree, M. J. (1994). Pilot-candidate selection method: Sources of validity. The International Journal of Aviation Psychology, 4(2), 103–117. https://doi.org/10.1207/s15327108ijap0402_1
Chandra, P. G. (2020). Modelling the e-waste mitigation strategies using Grey-theory and DEMATEL framework. Journal of Cleaner Production, 281, 124035. https://doi.org/10.1016/j.jclepro.2020.124035
Chidester, T. R., Helmreich, R. L., Gregorich, S. E., & Geis, C. E. (1991). Pilot personality and crew coordination: Implications for training and selection. The International Journal of Aviation Psychology, 1(1), 25–44. https://doi.org/10.1207/s15327108ijap0101_3
Dahooie, J. H., Dehshiri, S. J. H., Banaitis, A., & Binkytė-Vėlienė, A. (2020). Identifying and prioritizing cost reduction solutions in the supply chain by integrating value engineering and gray multi-criteria decision-making. Technological and Economic Development of Economy, 26(6), 1311–1338. https://doi.org/10.3846/tede.2020.13534
Damos, D. L. (1996). Pilot selection batteries: Shortcomings and perspectives. The International Journal of Aviation Psychology, 6(2), 199–209. https://doi.org/10.1207/s15327108ijap0602_6
Deng, J. L. (1982). Control problems of grey systems. Systems & Control Letters, 1(5), 288–294. https://doi.org/10.1016/S0167-6911(82)80025-X
Diamond, R. (1982). Pilot selection criteria for the AH-64 helicopter [Unpublished master dissertation, Naval Postgraduate School Monterey, University of Albuquerque]. California, USA.
Ergin, K. (2007). Helikopter uçucularında işitme kayıplarının incelenmesi [Unpublished master dissertation, Ankara University Health Sciences Institute]. Ankara, Turkey.
Griffin, G. R., & Koonce, J. M. (1996). Review of psychomotor skills in pilot selection research of the U. S. military services. The International Journal of Aviation Psychology, 6(2), 125–147. https://doi.org/10.1207/s15327108ijap0602_2
Keleş, M. K., Özdağoğlu, A., & Işıldak, B. (2021). An application with multi-criteria decision-making methods for the evaluation of airports from passengers’ view. Ankara Hacı Bayram Veli University Journal of the Faculty of Economics and Administrative Sciences, 23(2), 419–456.
Keršulienė, V., Zavadskas, E. K., & Turskis, Z. (2010). Selection of rational dispute resolution method by applying new step‐wise weight assessment ratio analysis (Swara). Journal of Business Economics and Management, 11(2), 243–258. https://doi.org/10.3846/jbem.2010.12
King, R. E. (2014). Personality (and psychopathology) assessment in the selection of pilots. The International Journal of Aviation Psychology, 24(1), 61–73. https://doi.org/10.1080/10508414.2014.860844
Köse, E., Aplak, H. S., & Kabak, M. (2013). Personel Seçimi için Gri Sistem Teori Tabanlı Bütünleşik Bir Yaklaşım. Ege Akademik Bakış, 13(4), 461–471. https://doi.org/10.21121/eab.2013418080
Milli Savunma Üniversitesi. (14 Jan 2021). Mezuniyet Sonrası Olanaklar. https://msu.edu.tr/sayfadetay?SayfaId=494&ParentMenuId=53
Mullins, W. R. (1993). Female combat helicopter pilot selection criteria [Unpublished master dissertation, Army Command and General Staff College Fort Leavenworth]. Kansas, USA.
Oktay, T., & Sultan, C. (2013). Constrained predictive control of helicopters. Aircraft Engineering and Aerospace Technology, 85(1), 32–47. https://doi.org/10.1108/00022661311294021
Oktay, T., & Sultan, C. (2015). Comfortable helicopter flight via passive/active morphing. IEEE Transactions on Aerospace and Electronic Systems, 51(4), 2876–2886. https://doi.org/10.1109/TAES.2015.140488
Özdağoğlu, A., & Keleş, M. K. (2019). The evaluation of BIST industrial enterprises from the viewpoint of banks – SWARA-GRA integrated approach. Suleyman Demirel University Visionary Journal, 10(24), 229–241. https://doi.org/10.21076/vizyoner.532727
Özdağoğlu, A., Keleş, M. K., & Işıldak, B. (2021). Cabin crew selection in civil aviation with fuzzy SWARA and fuzzy MARCOS methods. Gümüşhane University Journal of Social Sciences Institute, 12(2), 284–302.
Pamucar, D., Yazdani, M., Montero-Simo, M. J., Araque-Padilla, R. A., & Mohammed, A. (2021). Multi-criteria decision analysis towards robust service quality measurement. Expert Systems with Applications, 170, 114508. https://doi.org/10.1016/j.eswa.2020.114508
Park, C., Kim, S. C., Tak, H. S., Shin, S. M., & Choi, Y. C. (2019). The correlation between flight training factors in helicopter pilot training course and learning achievement. Journal of the Korean Society for Aviation and Aeronautics, 27(3), 45–53. https://doi.org/10.12985/ksaa.2019.27.3.045
Petrovic, J., & Petrovic, I. (2021). What makes a successful helicopter pilot? A fuzzy multi-criteria decision-making approach. International Journal for Traffic and Transport Engineering, 11(4), 507–527. https://doi.org/10.7708/ijtte2021.11(4).02
Ree, M. J., & Carretta, T. R. (1996). Central role of g in military pilot selection. The International Journal of Aviation Psychology, 6(2), 111–123. https://doi.org/10.1207/s15327108ijap0602_1
Siem, F. M. (1992). Predictive validity of an automated personality inventory for air force pilot selection. The International Journal of Aviation Psychology, 2(4), 261–270. https://doi.org/10.1207/s15327108ijap0204_2
Supçiller, A. A., & Bayramoğlu, S. (2020). Wind farm location selection with interval grey numbers based I-GRA and grey EDAS methods. Journal of the Faculty of Engineering and Architecture of Gazi University, 35(4), 1847–1860. https://doi.org/10.17341/gazimmfd.609518
Stanujkić, D., Karabašević, D., Popović, G., Stanimirović, P. S., Saračević, M., Smarandache, F., Katsikis, V. N., & Ulutaş, A. (2021). A new grey approach for using SWARA and PIPRECIA methods in a group decision-making environment. Mathematics, 9(13), 1554. https://doi.org/10.3390/math9131554
Ulutaş, A. (2021). A grey hybrid model to select the optimal third-party logistics provider. South African Journal of Industrial Engineering, 32(1), 171–181. https://doi.org/10.7166/32-1-2126
Ulutaş, A., & Karaköy, Ç. (2020). Evaluation of LPI values of transition economies countries with a grey MCDM model. In Handbook of research on applied AI for international business and marketing applications (Chapter 24, pp. 499–511). IGI Global. https://doi.org/10.4018/978-1-7998-5077-9.ch024
Weissmuller, J. J., & Damos, D. L. (2014). Improving the pilot selection system: Statistical approaches and selection processes. The International Journal of Aviation Psychology, 24(2), 99–118. https://doi.org/10.1080/10508414.2014.892764
Yazgan, E., & Erol, D. (2016). Determination of selection criteria for civil pilot candidates. Niğde University Journal of Engineering Sciences, 5(2), 97–104. https://doi.org/10.28948/ngumuh.294659