Airplane Selection to Renovate Air Transportation System: a Multi-Criteria Decision-Making Problem

Document Type : Original Article

Authors

1 Department of Civil and Environmental Engineering, Tarbiat Modares University, Tehran, Iran

2 Department of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran

Abstract

As one of the main infrastructures of the air transportation system, the air fleet has a significant effect on the operation at a reasonable cost. Deciding on the commensurate airplane to renovate the fleet falls into the multi-criteria decision-making (MCDM) problems. Airplane comparison criteria are very diverse, and no airplane is the best based on all criteria. In this study, selecting commensurate airplanes for airlines that meet domestic air transportation demand was investigated. The alternatives considered were Airbus airplanes, which were evaluated and compared based on six indices: price, maximum takeoff weight, passenger capacity, fuel capacity, the volume of passengers’ space, and volume of the cargo compartment. Also, several MCDM techniques require different levels of computational and maybe produce different outputs. The results of the different methods are not the same. To ensure consistency, accuracy and increase the reliability of the results, several methods were applied. Four different MCDM methods were used to make a comprehensive comparison, including analytic hierarchy process (AHP), simple additive weighting (SAW), and technique for order of preference by similarity to ideal solution (TOPSIS), and elimination et choice translating reality (ELECTRE). The results showed that the Airbus A318 airplane is selected as the top alternative based on these indices and using all four methods. The difference between the results of each method revealed for ranks 2-6. Based on AHP, TOPSIS and SAW, the second rank was designated to Airbus 319. However, ELECTRE had a different rank for this airplane.

Keywords

References

[1]-Loh, H. S., 2020, Airport selection criteria of low-cost carriers: A fuzzy analytical hierarchy process, Journal of Air Transport Management, 83,101759.
[2]-Du, Y., 2020, Decision-making method of heavy-duty machine tool remanufacturing based on AHP-entropy weight and extension theory, Journal of Cleaner Production, 252, 119607.
[3]-Batouei, A., 2020, Components of airport experience and their roles in eliciting passengers' satisfaction and behavioral intentions, Research in Transportation Business & Management, 37, 100585.
[4]-Celik, E. and Akyuz, E., 2018, An interval type-2 fuzzy AHP and TOPSIS methods for decision-making problems in maritime transportation engineering: the case of ship loader, Ocean Engineering, 155, 371-381.
[5]-Zaim, H., 2009, Analysing business competition by using ahp weighted topsis method: An example of turkish domestic aviation industry, in International Symposium on Sustainable Development, Citeseer.
[6]-Liu, Y., Eckert, C. M. and Earl, C., 2020, A review of fuzzy AHP methods for decision-making with subjective judgments, Expert Systems with Applications, 113738.
[7]-Janic, M. and Reggiani, A., 2002, An application of the multiple criteria decision making (MCDM) analysis to the selection of a new hub airport, European Journal of Transport and Infrastructure Research, 2(2/3), 121-134.
[8]-Dožić, S. and Kalić, M., 2014, An AHP approach to aircraft selection process, Transportation Research Procedia, 3, 165-174.
[9]-Dožić, S. and Kalić, M., 2015, Comparison of two MCDM methodologies in aircraft type selection problem, Transportation Research Procedia, 10, 910-919.
[10]-Hammond, J. S., Keeney, R. L. and Raiffa, H., 1998, Even swaps: A rational method for making trade-offs, Harvard business review, 76, 137-150.
[11]-Ozdemir, Y., Basligil, H., and Karaca, M., 2011, Aircraft selection using analytic network process: a case for Turkish airlines, in Proceedings of the World Congress on Engineering (WCE).
[12]-Čokorilo, O., 2010, Multi attribute decision making: Assessing the technological and operational parameters of an aircraft, Transport, 25(4), 352-356.
[13]-Hwang, C. L. and Masoud, A. S. M., 2012, Multiple objective decision making—methods and applications: a state-of-the-art survey, Springer Science & Business Media, 164.
[14]-Bruno, G., Esposito, E., and Genovese, A., 2015, A model for aircraft evaluation to support strategic decisions, Expert Systems with Applications, 42(13), 5580-5590.
[15]-Gomes, L. F. A. M., de Mattos Fernandes, J. E., and de Mello, J.C.C.S., 2014, A fuzzy stochastic approach to the multi criteria selection of an aircraft for regional chartering, Journal of Advanced Transportation, 48(3), 223-237.
[16]-Janic, M., 2015, A multi-criteria evaluation of solutions and alternatives for matching capacity to demand in an airport system: the case of London, Transportation Planning and Technology, 38(7), 709-737.
[17]-Lashgari, A., 2012, Equipment selection using fuzzy multi criteria decision making model: key study of Gole Gohar iron mine, Engineering economics, 23(2), 125-136.
[18]-Wang, Y., J. Zhu, and H. Sun, 2016, A decomposition approach to determining fleet size and structure with network flow effects and demand uncertainty, Journal of Advanced Transportation, 50(7), 1447-1469.
[19]-Zavadskas, E. K. and Z. Turskis, 2011, multiple criteria decision making (MCDM) methods in economics: an overview, Technological and economic development of economy, 17(2), 397-427.
[20]-Kazemi, A., Attari, M. Y. N. ,and Khorasani, M., 2016, Evaluating service quality of airports with integrating TOPSIS and VIKOR under fuzzy environment, International Journal of Services, Economics and Management, 7(2-4), 154-166.
[21]-Pamucar, D., 2021, Multi-criteria decision analysis towards robust service quality measurement, Expert Systems with Applications, 170, 114508.
[22]-Bakioglu, G. and Atahan, A. O., 2021, AHP integrated TOPSIS and VIKOR methods with Pythagorean fuzzy sets to prioritize risks in self-driving vehicles, Applied Soft Computing, 99, 106948.
[23]-Saaty, T. L., 2004, Decision making—the analytic hierarchy and network processes (AHP/ANP), Journal of systems science and systems engineering, 13(1), 1-35.
[24]-Zhou, H., Y. Li, and Y. Gu., 2021, Research on evaluation of airport service quality based on improved AHP and Topsis methods. In Proceedings of the Institution of Civil Engineers-Transport. Thomas Telford Ltd.
[25]-Anggraeni, E. Y., 2018, Poverty level grouping using SAW method, International Journal of Engineering and Technology, 7(2.27), 218-224.
[26]-Keskin, B. and E. Ulas, 2017, Does privatization affect airports performance? A comparative analysis with AHP-TOPSIS and DEA, in new trends in finance and accounting, 335-345.
[27]-Opricovic, S. and G.-H. Tzeng, 2004, Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS, European journal of operational research, 156(2), 445-455.
[28]-Kou, G., 2012, Evaluation of classification algorithms using MCDM and rank correlation, International Journal of Information Technology & Decision Making, 11(01), 197-225.
Advance Researches in Civil Engineering
Volume 3, Issue 3
September 2021
Pages 61-75

Files

Share

How to cite

Statistics