Trainer Aircraft Selection Using Preference Analysis for Reference Ideal Solution (PARIS)

Authors: C. Ardil

Abstract:

This article presents a multiple criteria evaluation for a trainer aircraft selection problem using "preference analysis for reference ideal solution (PARIS)” approach. The available relevant literature points to the use of multiple criteria decision making analysis (MCDMA) methods for the problem of trainer aircraft selection, which often involves conflicting multiple criteria. Therefore, this MCDMA study aims to propose a robust systematic integrated framework focusing on the trainer aircraft selection problem. For this purpose, an integrated preference analysis approach based the mean weight and entropy weight procedures with PARIS, and TOPSIS was used for a MCDMA compensating solution. In this study, six trainer aircraft alternatives were evaluated according to six technical decision criteria, and data were collected from the current relevant literature. As a result, the King Air C90GTi alternative was identified as the most suitable trainer aircraft alternative. In order to verify the stability and accuracy of the results obtained, comparisons were made with existing MCDMA methods during the sensitivity and validity analysis process.The results of the application were further validated by applying the comparative analysis-based PARIS, and TOPSIS method. The proposed integrated MCDMA systematic structure is also expected to address the issues encountered in the aircraft selection process. Finally, the analysis results obtained show that the proposed MCDMA method is an effective and accurate tool that can help analysts make better decisions.

Keywords: aircraft, trainer aircraft selection, multiple criteria decision making, multiple criteria decision making analysis, mean weight, entropy weight, MCDMA, PARIS, TOPSIS

References:

[1] Chou, S.Y., Chang, Y.H. and Shen, C.Y. (2008). A fuzzy simple additive weighting system under group decision-making for facility location selection with objective/subjective attributes. European Journal of Operational Research, Vol. 189 No. 1, pp. 132-145.
[2] Abdel-malak, F.F., Issa, U.H., Miky, Y.H., Osman, E.A. (2017) Applying decision-making techniques to Civil Engineering Projects. Beni-Suef University Journal of Basic and Applied Sciences, 6, 326-331.
[3] Mardani, A., Jusoh, A., Md Nor, K., Khalifah, Z, Zakwan, N., Valipour, A. (2015) Multiple criteria decision-making techniques and their applications – a review of the literature from 2000 to 2014. Economic Research-Ekonomska Istraživanja, 28, 516-571.
[4] Mardani, A., Jusoh, A., Zavadskas, E.K., Kazemilari, M.; Ungku, N.U.A., Khalifah, Z. (2016) Application of Multiple Criteria Decision Making Techniques in Tourism and Hospitality Industry: a Systematic Review. Transformations in Business & Economics, 15, 192-213.
[5] Mardani, A., Jusoh, A., Zavadskas, E.K.; Khalifah, Z., Nor, K.M.D. (2015) Application of multiple-criteria decision-making techniques and approaches to evaluating of service quality: a systematic review of the literature. Journal of Business Economics and Management, 16, 1034-1068.
[6] Turskis, Z., Morkunaite, Z., Kutut, V. (2017) A hybrid multiple criteria evaluation method of ranking of cultural heritage structures for renovation projects. International Journal of Strategic Property Management, 21, 318-329.
[7] Turskis, Z., Juodagalvienė, B. (2016) A novel hybrid multi-criteria decision-making model to assess a stairs shape for dwelling houses. Journal of Civil Engineering and Management, 22, 1078-1087.
[8] Trinkūnienė, E., Podvezko, V., Zavadskas, E.K., Jokšienė, I., Vinogradova, I., Trinkūnas, V. (2017) Evaluation of quality assurance in contractor contracts by multi-attribute decision-making methods. Economic Research-Ekonomska Istraživanja, 30, 1152-1180.
[9] Choudhary, D. and Shankar, R. (2012. A STEEP-fuzzy AHP-TOPSIS framework for evaluation and selection of thermal power plant location: a case study from India”, Energy, Vol. 42 No. 1, pp. 510-521.
[10] Chu, T.C. (2002. Facility location selection using fuzzy TOPSIS under group decisions”, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, Vol. 10 No. 6, pp. 687-701.
[11] Hwang, C.L.; Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications. New York: Springer-Verlag.
[12] Zavadskas, E.K., Mardani, A., Turskis, Z., Jusoh, A., Nor, K.M. (2016) Development of TOPSIS method to solve complicated decision-making problems: An overview on developments from 2000 to 2015. International Journal of Information Technology & Decision Making, 15, 645-682.
[13] Opricovic, S., Tzeng, G-H., (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research,vol. 156(2), 445-455.
[14] Opricovic, S., Tzeng, G.-H. (2007). Extended VIKOR method in comparison with outranking methods. European Journal of Operational Research, vol. 178(2), 514-529.
[15] Mardani, A., Zavadskas, E., Govindan, K., Amat Senin, A., Jusoh, A. (2016) VIKOR Technique: A Systematic Review of the State of the Art Literature on Methodologies and Applications. Sustainability, 8, 37.
[16] Fei, L., Xia, J., Feng, Y., Liu, L. (2019) An ELECTRE-Based Multiple Criteria Decision Making Method for Supplier Selection Using Dempster-Shafer Theory. IEEE Access, 7, 84701-84716.
[17] Brans, J., Ph. Vincke. (1985) A Preference Ranking Organisation Method: (The PROMETHEE Method for Multiple Criteria Decision-Making). Management Science, 31(6), 647-656. Retrieved June 28, 2021, from http://www.jstor.org/stable/2631441.
[18] Brans, J.P., Vincke, Ph., Mareschal, B., (1986) How to select and how to rank projects: the PROMETHEE method. European Journal of Operational Research, 24, 228-238.
[19] Brans, J.P., Macharis, C., Kunsch, P.L., Chevalier, A., Schwaninger, M., (1998). Combining multicriteria decision aid and system dynamics for the control of socio-economic processes. An iterative real-time procedure. European Journal of Operational Research 109, 428-441.
[20] Brans, J.P. and Mareschal, B., (2005). Chapter 5: PROMETHEE methods, 164-195.
[21] Ardil, C., Bilgen, S. (2017) Online Performance Tracking. SocioEconomic Challenges, 1(3), 58-72. ISSN (print) – 2520-6621.
[22] Ardil, C. (2018) Multidimensional Performance Tracking. International Journal of Computer and Systems Engineering, Vol:12, No:5,320-349
[23] Ardil, C. (2018) Multidimensional Compromise Optimization for Development Ranking of the Gulf Cooperation Council Countries and Turkey. International Journal of Mathematical and Computational Sciences Vol:12, No:6, 131-138.
[24] Ardil, C. (2018) Multidimensional Compromise Programming Evaluation of Digital Commerce Websites. International Journal of Computer and Information Engineering Vol:12, No:7, 556-563.
[25] Ardil, C. (2018) Multicriteria Decision Analysis for Development Ranking of Balkan Countries. International Journal of Computer and Information Engineering Vol:12, No:12, 1118-1125.
[26] Ardil, C. (2019) Scholar Index for Research Performance Evaluation Using Multiple Criteria Decision Making Analysis. International Journal of Educational and Pedagogical Sciences, Vol:13, No:2, 93-105.
[27] Ardil, C. (2020) Facility Location Selection using Preference Programming. International Journal of Industrial and Systems Engineering, 14(1), 1 - 12.
[28] See,T.-K., Gurnani, A., Lewis, K. E. (2004) Multi-Attribute Decision Making Using Hypothetical Equivalents and Inequivalents. Transactions of the ASME, Vol. 126, p. 950-958.
[29] Wang, T. C., Chang, T. H. (2007) Application of TOPSIS in evaluating initial training aircraft under a fuzzy environment. Expert Systems with Applications, 33, 870-880.
[30] Ozdemir, Y., Basligil, H., Karaca, M. (2011) Aircraft Selection Using Analytic Network Process: A Case for Turkish Airlines. Proceedings of the World Congress on Engineering, Vol II, London, U.K. July 6-8. http://www.iaeng.org/publication/WCE2011/WCE2011_pp1155-1159.pdf)
[31] Gomes, L. F. A. M., Fernandes, J. E. d. M., Soares de Mello, J. C. C. B. (2012) A fuzzy stochastic approach to the multicriteria selection of an aircraft for regional chartering. Journal of Advanced Transportation, p.223-237.
[32] Dožić, S., Kalić, M. (2014) An AHP approach to aircraft selection process.Transportation Research Procedia 3, p.165 – 174.
[33] Teoh, L. E., Khoo, H. L. (2015) Airline Strategic Fleet Planning Framework. Journal of the Eastern Asia Society for Transportation Studies, 11, p. 2258-2276.
[34] Sánchez-Lozano, J. M., Serna, J., Dolón-Payán, A. (2015) Evaluating military training aircrafts through the combination of multi-criteria decision making processes with fuzzy logic. A case study in the Spanish Air Force Academy. Aerospace Science and Technology, Volume 42, p. 58-65.
[35] Dožić, S., Kalić, M. (2015) Comparison of two MCDM methodologies in aircraft type selection problem. Transportation Research Procedia 10, p. 910 – 919.
[36] Ozdemir, Y., Basligil, H. (2016) Aircraft selection using fuzzy ANP and the generalized choquet integral method: The Turkish airlines case. Journal of Intelligent and Fuzzy Systems, 31(1), p. 589-600.
[37] Golec, A., Gurbuz, F., Senyigit, E. (2016) Determination of best military cargo aircraft with multicriteria decision making techniques. MANAS Journal of Social Studies, Vol. 5, No. 5, p.87-101.
[38] Silva, M. A., Eller, R. d. A. G., Alves, C. J. P., Caetano, M. (2016) Key factors in aircraft assessment and fleet planning: a multicriteria approach Analytic Hierarchy Process. Journal of the Brazilian air transportation research society, Volume 12(1), p.45-53.
[39] Ali,Y., Muzzaffar, A. A., Muhammad, N., Salman, A. (2017) Selection of a fighter aircraft to improve the effectiveness of air combat in the war on terror: Pakistan Air Force - a case in point. International Journal of the Analytic Hierarchy Process, Vol. 9(2), p. 244-273.
[40] Dozic, S., Lutovac,T., Kalic, M. (2018) Fuzzy AHP approach to passenger aircraft type selection. Journal of Air Transport Management, Vol: 68, p.165-175.
[41] Ki̇raci, K, Bakir, M. (2018) Application of commercial aircraft selection in aviation industry through multi-criteria decision making methods. Manisa Celal Bayar University Journal of Social Sciences, 16 (4), p.307-332.
[42] Kiraci, K., Bakir, M. (2018) Using the Multi Criteria Decision Making Methods in Aircraft Selection Problems and an Application. Journal of Transportation and Logistics, 3(1), p. 13-24.
[43] Ilgin, M. A. (2019) Aircraft Selection Using Linear Physical Programming. Journal of Aeronautics and Space Technologies, Vol.12, No.2, p.121-128.
[44] Ardil, C. (2019) Military Fighter Aircraft Selection Using Multiplicative Multiple Criteria Decision Making Analysis Method. International Journal of Mathematical and Computational Sciences, 13(9), 184 - 193.
[45] Ardil, C. (2019) Fighter Aircraft Selection Using Technique for Order Preference by Similarity to Ideal Solution with Multiple Criteria Decision Making Analysis. International Journal of Transport and Vehicle Engineering, Vol:13, No:10, 649-657.
[46] Ardil, C., Pashaev, A. M., Sadiqov, R.A., Abdullayev, P. (2019) Multiple Criteria Decision Making Analysis for Selecting and Evaluating Fighter Aircraft. International Journal of Transport and Vehicle Engineering, Vol:13, No:11, 683-694.
[47] Ardil, C. (2019) Aircraft Selection Using Multiple Criteria Decision Making Analysis Method with Different Data Normalization Techniques. International Journal of Industrial and Systems Engineering, Vol:13, No:12, 744-756.
[48] Ardil, C. (2020) Aircraft Selection Process Using Preference Analysis for Reference Ideal Solution (PARIS). International Journal of Aerospace and Mechanical Engineering, 14(3), 80 - 90.
[49] Sánchez-Lozano, J.M., Rodríguez, O.N. (2020) Application of Fuzzy Reference Ideal Method (FRIM) to the military advanced training aircraft selection. Appl. Soft Comput., 88, 106061.
[50] Yilmaz, A.K., Malagas, K., Jawad, M., Nikitakos, N. (2020) Aircraft selection process with technique for order preference by similarity to ideal solution and AHP integration. Int. J. Sustainable Aviation, Vol. 6, No. 3, 220-235.
[51] Kiraci, K., Akan, E. (2020) Aircraft selection by applying AHP and TOPSIS in interval type-2 fuzzy sets. Journal of Air Transport Management, 89, 101924 - 101924.
[52] Shannon C.E. (1948) A mathematical theory of communication. The Bell System Technical Journal, Vol. 27, pp. 379–423, 623–656.