Prioritizing flight simulators of the brazilian air force by the analytic hierarchy process and hypothesis tests




Flight simulators, Brazilian Air Force, AHP, Hypothesis test


Goal: The purpose of the research is to apply a method of decision support to prioritize flight simulators of the Air Force Command in view of the country”s budget constraints in the defense sector.

Methodology: The research was performed with the Analytic Hierarchy Process (AHP), associated with hypothesis tests to define the preference or equivalence relationships between the simulators. Data collection involved the support of 32 Air Force specialists with extensive experience in the chosen simulators.

Results: The T-27 Tucano simulator was preferred, followed by the C-95M Bandeirantes and the C-105 Amazonas, which obtained statistical similarity to each other. In fourth place was the A-29 Super Tucano simulator. The two simulators that had the least preference were the F-5M Tiger II and the A-1 AMX, which achieved results that were statistically close to each other.

Limitations: Any multicriteria decision aid technique embeds its features and limitations. This is not exclusive to AHP, although the consistency ratio is a differential in relation to other methods. The expert sample also reflects the preferences of a group, with reservations to the generalization of the results.

Practical implications: The findings of this research can be used in practice, by assisting the Brazilian Air Force in applying its scarce financial resources to prioritize flight simulators.

Originality / Value: The research is unique to the Brazilian Air Force, in particular to the Center that oversees flight simulators, and is also relevant in including hypothesis testing to AHP results.


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Abastante, F. et al. (2019), “A new parsimonious AHP methodology: assigning priorities to many objects by comparing pairwise few reference objects”, Expert Systems with Applications, Vol.127, pp. 109–120.

Agápito, A. O. et al. (2015), “Utilização do método de análise hierárquica (ahp) como ferramenta de auxílio multicritério no processo de decisão de priorização de projetos de ciência, tecnologia e inovação na Amazônia azul”, in XVIII Simpósio de Pesquisa Operacional e Logística da Marinha. Rio de Janeiro-RJ: Marinha do Brasil, pp. 1–10,

Agápito, A. de O. et al. (2019) “Using multicriteria analysis and fuzzy logic for project portfolio management”, Brazilian Journal of Operations & Production Management, Vol. 16, No. 2, pp. 347–357.

Alonso, S. et al. (2008), “A consistency‐based procedure to estimate missing pairwise preference values”, International journal of intelligent systems, 23(2), pp. 155–175.

Alonso, S. et al. (2009), “Group decision making with incomplete fuzzy linguistic preference relations”, International Journal of Intelligent Systems, Vol. 24, No. 2, pp. 201–222.

Arnaut, B. M. et al. (2012), “Multimetodologias na identificação, seleção e priorização de projetos de P&D no setor de defesa”, in XIV Simpósio de Aplicações Operacionais em Áreas de Defesa. São José dos Campos - SP: Instituto Tecnológico da Aeronáutica, pp. 1–8,

Ateş, M. and Önder, D. E. (2021), “A local smart city approach in the context of smart environment and urban resilience”, International Journal of Disaster Resilience in the Built Environment,

Balusa, B. C. and Gorai, A. K. (2019), “Sensitivity analysis of fuzzy-analytic hierarchical process (FAHP) decision-making model in selection of underground metal mining method”, Journal of Sustainable Mining, Vol. 18, No. 1, pp. 8–17.

Bass, L., Clements, P. and Kazman, R. (2003), Software architecture in practice. Addison Wesley Professional.

Bent, J. and Chan, K. (2010), “Flight training and simulation as safety generators”, in Human factors in aviation. Elsevier, pp. 293–334.

Bezerra, T. A. R. et al. (2020), “Data Acquisition System for Revitalization of Aircraft EMB 312 T-27 and AT-29 Force Simulator”, International Journal of Astronautics and Aeronautical Engineering, Vol. 5, pp. 1–9.

Bimo, E. A. et al. (2022), “The Application of AHP and PESTEL-SWOT analysis on the study of military amphibious aircraft acquisition decision making in Indonesia”, Technium Social Sciences Journal, Vol. 27, pp. 837–853.

Brazil (2018a) “Comando da Aeronáutica. Portaria no 1.597/GC3, de 10 de outubro de 2018. Aprova a reedição da DCA 11-45 “Concepção Estratégica - Força Aérea 100".”, Boletim do Comando da Aeronáutica, 180(11265).

Brazil (2018b), “Comando da Aeronáutica. Portaria no 2.102/GC3, de 18 de dezembro de 2018. Aprova a reedição da PCA 11-47 “Plano Estratégico Militar da Aeronáutica 2018 - 2027"“, Boletim do Comando da Aeronáutica, 222(14766).

Camilo, J. A. P.; Gavião, L. O. and Kostin, S. (2020), “Priorização de projetos do segmento espacial por processo de análise hierárquica”, Revista Brasileira de Estudos de Defesa, 7(1). Chakrabarty, D. (2021), “Measuremental Data: Seven Measures of Central Tendency”, International Journal of Electronics, Vol. 8, No. 1.

Ellman, J. et al. (2016), “Defense Acquisition Trends, 2015: Acquisition in the Era of Budgetary Constraints”, 1st edn. Edited by C. for S. & I. Studies. Washington, DC: Rowman & Littlefield. Emre, A. M. (2016), “Analysis of the Benefits of Motion Simulators in 5th Generation Fighter Pilots Training”, International Journal of Educational and Pedagogical Sciences, Vol. 10, No. 2, pp. 411–415.

Gavião, L. O., Lima, G. B. A. and Garcia, P. A. de A. (2021), “Procedimento de redução das avaliações do AHP por transitividade da escala verbal de Saaty”, in Senhoras, E. M. (ed.) Engenharia de Produção: além dos produtos e sistemas produtivos. 1st edn. Ponta Grossa - PR: Editora Atena, pp. 88–102,

Goswami, S. S., Behera, D. K. and Mitra, S. (2020), “A Comprehensive Study of Weighted Product model for selecting the best product in our daily life”, Brazilian Journal of Operations & Production Management, Vol. 17, No. 2, pp. 1–18.

Hamurcu, M. and Eren, T. (2020), “Selection of Unmanned Aerial Vehicles by Using Multicriteria Decision-Making for Defence”, Journal of Mathematics, 2020.

Janzwood, S. (2021), “R&D priority-setting for global catastrophic risks: The case of the NASA planetary defense mission”, Research Policy, Vol. 50, N. 6, p. 104225.

Junior, J. C. P. and Garcia, C. M. (2021), “Voo de instrução: importância do uso de simulador de voo para a formação de piloto”, Revista Brasileira de Aviação Civil & Ciências Aeronáuticas, Vol. 1, No. 2, pp. 164–191.

Lee, D., McCool, J. and Napieralski, L. (2000), “Assessing adult learning preferences using the analytic hierarchy process”, International Journal of Lifelong Education, Vol. 19, No. 6, pp. 548–560.

Li, C.-C. et al. (2019), “An overview on managing additive consistency of reciprocal preference relations for consistency-driven decision making and fusion: Taxonomy and future directions”, Information Fusion, Vol. 52, pp. 143–156.

Lin, C., Kou, G. and Ergu, D. (2013), “An improved statistical approach for consistency test in AHP”, Annals of Operations Research, Vol. 211, No. 1, pp. 289–299.

Liu, C. H. and Lin, C.-W. R. (2016), “The Comparative of the AHP Topsis Analysis Was Applied for the Commercialization Military Aircraft Logistic Maintenance Establishment”, International Business Management, Vol. 10, No. 4, pp. 6428–6432.

Matos, P. V. et al. (2018), “The use of multi-criteria analysis in the recovery of abandoned mines: a study of intervention in Portugal”, RAUSP Management Journal, Vol. 53, pp. 214–224.

Mavin, T. J., Kikkawa, Y. and Billett, S. (2018), “Key contributing factors to learning through debriefings: commercial aviation pilots” perspectives”, International Journal of Training Research, Vol. 16, N. 2, pp. 122–144.

Mendes, J. B., Brandao-Ramos, A. C. and Mora-Camino, F. (2014), “Low Cost Helicopter Training Simulator: A Software Case Study from the Brazilian Military Police”, International Journal of Computer Science and Artificial Intelligence, Vol. 4, No. 2, pp. 45–53.

Mufazzal, S. et al. (2021), “Towards minimization of overall inconsistency involved in criteria weights for improved decision making”, Applied Soft Computing, 100, p. 106936.

Rodrigues, A. (2021), “Orçamento atende a metade das necessidades da Defesa, diz ministro”, Agência Brasil, 5 May, p. 1,

Sá, F. R. de, Vieira, R. G. and Cunha, A. M. da (2022), “Learning Lessons From the Scrum Adoption in the Brazilian Air Force”, IT Professional, Vol. 24, No. 1, pp. 49–55.

Saaty, T. L. (1980) The Analytic Hierarchy Process. New York: McGraw-Hill.

Salgado, F. A. S. (2021), Proposta de modelo para seleção de navios de pesquisa Antártica por método AHP-TOPSIS e Planejamento Baseado por Capacidades. Brazilian War College.

Santos, M. dos, Costa, I. P. de A. and Gomes, C. F. S. (2021), “Multicriteria decision-making in the selection of warships: a new approach to the AHP method”, International Journal of the Analytic Hierarchy Process, Vol. 13, No. 1, pp. 147–169.

Silva, A. C., Belderrain, M. C. N. and Pantoja, F. C. M. (2010), “Prioritization of R&D projects in the aerospace sector: AHP method with ratings”, Journal of Aerospace Technology and Management, Vol. 2, pp. 339–348.

Silva, M. H. de O. C. et al. (2021), “Mental Workload Assessment in Military Pilots Using Flight Simulators and Physiological Sensors”, in International Symposium on Human Mental Workload: Models and Applications. Springer, pp. 99–115.

Silva, R. Q. (2019), “Orçamento da defesa nacional de 2010 a 2018: análises e perspectivas”, Expediente, 9(1), pp. 74–96.

Simplício, R., Gomes, J. and Romão, M. (2017), “Projects selection and prioritization: a Portuguese Navy pilot model”, Procedia Computer Science, Vol. 121, pp. 72–79.

Souza, G. M. et al. (2022), “Integrating fuzzy-MCDM methods to select project portfolios under uncertainty: the case of a pharmaceutical company”, Brazilian Journal of Operations & Production Management, Vol. 19, No. 3, pp. 1–19.

Stein, W. E. and Mizzi, P. J. (2007), “The harmonic consistency index for the analytic hierarchy process”, European Journal of Operational Research, Vol. 177, No. 1, pp. 488–497.

Stromgren, C. et al. (2018), “Investment portfolio prioritization for emerging homeland security threats”, in 2018 Winter Simulation Conference (WSC). IEEE, pp. 2769–2780.

Vidakovic, J. et al. (2021), “Flight Simulation Training Devices: Application, Classification, and Research”, International Journal of Aeronautical and Space Sciences, pp. 1–12.

Vogel, R. M. (2022), “The geometric mean?”, Communications in Statistics-Theory and Methods, Vol. 51, No. 1, pp. 82–94.

Wind, Y. and Saaty, T. L. (1980), “Marketing Applications of the Analytic Hierarchy Process.”, Management Science, Vol. 26, No. 7, pp. 641–658,

Zheng, N. and Ma, G. (2018) “Analytic Hierarchy Process Improvement”, International Journal of Engineering and Applied Sciences, Vol. 5, No. 4, p. 257229.

Zheng, S. et al. (2009) “Flight simulator architecture development and implementation”, in 2009 International Conference on Measuring Technology and Mechatronics Automation. IEEE, pp. 230–233.




How to Cite

Assis, S. R. de, Gavião, L. O., Kostin, S. ., & Lima, G. B. A. (2022). Prioritizing flight simulators of the brazilian air force by the analytic hierarchy process and hypothesis tests. Brazilian Journal of Operations & Production Management, 19(4), 1366.



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