Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 31903
Aircraft Selection Using Multiple Criteria Decision Making Analysis Method with Different Data Normalization Techniques

Authors: C. Ardil


This paper presents an original application of multiple criteria decision making analysis theory to the evaluation of aircraft selection problem. The selection of an optimal, efficient and reliable fleet, network and operations planning policy is one of the most important factors in aircraft selection problem. Given that decision making in aircraft selection involves the consideration of a number of opposite criteria and possible solutions, such a selection can be considered as a multiple criteria decision making analysis problem. This study presents a new integrated approach to decision making by considering the multiple criteria utility theory and the maximal regret minimization theory methods as well as aircraft technical, economical, and environmental aspects. Multiple criteria decision making analysis method uses different normalization techniques to allow criteria to be aggregated with qualitative and quantitative data of the decision problem. Therefore, selecting a suitable normalization technique for the model is also a challenge to provide data aggregation for the aircraft selection problem. To compare the impact of different normalization techniques on the decision problem, the vector, linear (sum), linear (max), and linear (max-min) data normalization techniques were identified to evaluate aircraft selection problem. As a logical implication of the proposed approach, it enhances the decision making process through enabling the decision maker to: (i) use higher level knowledge regarding the selection of criteria weights and the proposed technique, (ii) estimate the ranking of an alternative, under different data normalization techniques and integrated criteria weights after a posteriori analysis of the final rankings of alternatives. A set of commercial passenger aircraft were considered in order to illustrate the proposed approach. The obtained results of the proposed approach were compared using Spearman's rho tests. An analysis of the final rank stability with respect to the changes in criteria weights was also performed so as to assess the sensitivity of the alternative rankings obtained by the application of different data normalization techniques and the proposed approach.

Keywords: Normalization Techniques, Aircraft Selection, Multiple Criteria Decision Making, Multiple Criteria Decision Making Analysis, MCDMA

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 287


[1] 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.
[2] 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.
[3] 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.
[4] 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.
[5] Dožić, S., Kalić, M. (2014) An AHP approach to aircraft selection process.Transportation Research Procedia 3, p.165 – 174.
[6] 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.
[7] 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.
[8] Dožić, S., Kalić, M. (2015) Comparison of two MCDM methodologies in aircraft type selection problem. Transportation Research Procedia 10, p. 910 – 919.
[9] 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.
[10] 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.
[11] 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.
[12] 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.
[13] 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.
[14] 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.
[15] 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.
[16] Ilgin, M. A. (2019) Aircraft Selection Using Linear Physical Programming. Journal of Aeronautics and Space Technologies, Vol.12, No.2, p.121-128.
[17] Velasquez, M., Hester, P. T. (2013) An Analysis of Multi-Criteria Decision Making Methods. International Journal of Operations Research Vol. 10, No. 2, p.56-66.
[18] Mardani, A., Jusoh, A., Nor, K. MD., Khalifah, Z., Zakwan, N., Valipour, V. (2015) Multiple criteria decision-making techniques and their applications – a review of the literature from 2000 to 2014. Economic Research-Ekonomska Istraživanja, 28:1, p. 516-571.
[19] Mardani, A., Zavadskas, E. K., Khalifah, Z., Jusoh, A., Nor, K. MD. (2016) Multiple criteria decision-making techniques in transportation systems: a systematic review of the state of the art literature, Transport, 31:3, p.359-385.
[20] Shannon, C.E. (1948) A mathematical theory of communication. The Bell System Technical Journal, Vol. 27, pp. 379–423, 623–656.
[21] Lotfi, F. H.,Fallahnejad, R. (2010) Imprecise Shannon’s Entropy and Multi Attribute Decision Making. Entropy, 12, p. 53-62.
[22] Diakoulaki, D, Mavrotas, G.,Papayannakis, L. (1992) A multicriteria approach for evaluating the performance of industrial firms. Omega. Vol. 20(4), p.467-474.
[23] Opricovic, S., Tzeng, G.-H. (2004) Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, 156, p.445–455.
[24] Cinelli, M., Coles, S. R., Kirwan, K. (2014) Analysis of the potentials of multi criteria decision analysis methods to conduct sustainability assessment. Ecological Indicators, 46, p. 138–148.
[25] Jato-Espino, D., Castillo-Lopez, E., Rodriguez-Hernandez, J., Canteras-Jordanac, J. C. (2014) A review of application of multi-criteria decision making methods in construction. Automation in Construction, Vol. 45, p. 151-162.
[26] Yalcin, N., Unlu, U. (2018) A multi-criteria performance analysis of initial public offering (IPO) firms using CRITIC and VIKOR methods. Technological and economic development of economy, Vol. 24(2): 534–560.
[27] Vinogradova, I., Podvezko, V., Zavadskas, E. K. (2018) The Recalculation of the Weights of Criteria in MCDM Methods Using the Bayes Approach. Symmetry, 10(6), 205.
[28] Calvo, T., Kolesarova, A., Komornikova, M., Mesiar, R. (2002) Aggregation Operators: Properties, Classes and Construction Methods. In: Calvo T., Mayor G., Mesiar R. (eds) Aggregation Operators. Studies in Fuzziness and Soft Computing, vol 97. Physica, Heidelberg.
[29] Poff, B., Tecle, A., Neary, D. G., Geils, B. (2010) Compromise Programming in forest management. Journal of the Arizona-Nevada Academy of Science. 42(1): 44-60.
[30] Butler,J., Morrice, D. J., Mullarkey, P. W. (2001) A Multiple Attribute Utility Theory Approach to Ranking and Selection. Management Science 47 (6) 800-816
[31] Yager, R. R. (2004) Decision making using minimization of regret. International Journal of Approximate Reasoning, Vol. 36 (2), 109-128.
[32] Vannucci, M., Stingo, F., Berzuini, C. (2012) Bayesian Models for Variable Selection that Incorporate Biological Information. DOI:10.1093/ACPROF:OSO/9780199694587.003.0022.
[33] Pimentel, R.S. (2009) Kendall's Tau and Spearman's Rho for Z s Rho for Zero-Inflated Data. PhD Dissertation, Western Michigan University, USA.
[34] Çelen, A. (2014) Comparative Analysis of Normalization Procedures in TOPSIS Method: With an Application to Turkish Deposit Banking Market, Informatica 25, no. 2, 185-208, DOI 10.15388/Informatica.2014.10.
[35] Vafaei N., Ribeiro R.A., Camarinha-Matos L.M. (2016) Normalization Techniques for Multi-Criteria Decision Making: Analytical Hierarchy Process Case Study. In: Camarinha-Matos L.M., Falcão A.J., Vafaei N., Najdi S. (eds) Technological Innovation for Cyber-Physical Systems. DoCEIS 2016. IFIP Advances in Information and Communication Technology, vol 470. Springer, Cham.
[36] Ardil, C., Bilgen, S. (2017) Online Performance Tracking. SocioEconomic Challenges, 1(3), 58-72.
[37] Ardil, C. (2018) Multidimensional Performance Tracking. International Journal of Computer and Systems Engineering, Vol:12, No:5,320-349
[38] 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.
[39] Ardil, C. (2018) Multidimensional Compromise Programming Evaluation of Digital Commerce Websites. International Journal of Computer and Information Engineering Vol:12, No:7, 556-563.
[40] 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.
[41] 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.
[42] 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.
[43] 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.
[44] 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.