Modeling Uncertainty in Multiple Criteria Decision Making Using the Technique for Order Preference by Similarity to Ideal Solution for the Selection of Stealth Combat Aircraft
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Modeling Uncertainty in Multiple Criteria Decision Making Using the Technique for Order Preference by Similarity to Ideal Solution for the Selection of Stealth Combat Aircraft

Authors: C. Ardil

Abstract:

Uncertainty set theory is a generalization of fuzzy set theory and intuitionistic fuzzy set theory. It serves as an effective tool for dealing with inconsistent, imprecise, and vague information. The technique for order preference by similarity to ideal solution (TOPSIS) method is a multiple-attribute method used to identify solutions from a finite set of alternatives. It simultaneously minimizes the distance from an ideal point and maximizes the distance from a nadir point. In this paper, an extension of the TOPSIS method for multiple attribute group decision-making (MAGDM) based on uncertainty sets is presented. In uncertainty decision analysis, decision-makers express information about attribute values and weights using uncertainty numbers to select the best stealth combat aircraft.

Keywords: Uncertainty set, stealth combat aircraft selection multiple criteria decision-making analysis, MCDM, uncertainty decision analysis, TOPSIS

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[1] Zadeh L.A., (1965). Fuzzy Sets. Information and Control, 8, 338-353.
[2] Zadeh L.A., (1975). The concept of a linguistic variable and its application to approximate reasoning III, Information sciences, vol. 9, no. 1, pp. 43–80.
[3] Atanasov, K.T. (1986). Intuitionistic fuzzy sets. Fuzzy sets and systems, 20, 87-96.
[4] Atanasov, K.T. (1989). More on intuitionistic fuzzy sets,” Fuzzy sets and systems, vol. 33, no. 1, 37–45.
[5] Atanassov, K.T., Gargov, G. (1989). Interval valued intuitionistic fuzzy sets. Fuzzy Sets and Systems, Volume 31, Issue 3, 343-349.
[6] Mizumoto, M., Tanaka, K. (1976). Some Properties of Fuzzy Sets of Type-2. Information and Control, 31, 312-340.
[7] Torra, V. (2010). Hesitant fuzzy sets. International Journal of Intelligent Systems, 25(6):529-539.
[8] Cuong, B.C. (2014). Picture fuzzy sets. Journal of Computer Science and Cybernetics, V.30, N.4 (2014), 409–420.
[9] Smarandache, F. (2019). Neutrosophic Set is a Generalization of Intuitionistic Fuzzy Set, Inconsistent Intuitionistic Fuzzy Set (Picture Fuzzy Set, Ternary Fuzzy Set), Pythagorean Fuzzy Set, Spherical Fuzzy Set, and q-Rung Orthopair Fuzzy Set, while Neutrosophication is a Generalization of Regret Theory, Grey System Theory, and Three-Ways Decision (revisited). Journal of New Theory, (29), 1-31.
[10] Ardil, C. (2024). Uncertainty Multiple Criteria Decision Making Analysis for Stealth Combat Aircraft Selection. International Journal of Aerospace and Mechanical Engineering, 18(4), 116 - 124.
[11] Hwang, C., Yoon, K. (1981). Multiple Attribute Decision Making. Springer, New York, 1981, vol. 186.
[12] Chen, C.-T. (2000). Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy sets and systems, vol. 114, no. 1, pp. 1–9.
[13] Jin, F., Liu, P.D., X. Zhang, X. (2007). Evaluation study of human resources based on intuitionistic fuzzy set and TOPSIS method, Journal of Information and Computational Science 4(3), 1023-1028.
[14] Wei, Y., Liu, P. (2009). Risk evaluation method of high-technology based on uncertain linguistic variable and TOPSIS method. Journal of computers, vol. 4, no. 3, 276–282.
[15] Liu, P. (2009). Multi-attribute decision-making method research based on interval vague set and TOPSIS method. Technological and economic development of economy, vol. 15, no. 3, 453–463.
[16] Liu, P., Su, Y. (2010). The extended TOPSIS based on trapezoid fuzzy linguistic variables, Journal of Convergence Information Technology, vol. 5, no. 4, pp. 38–53.
[17] Verma, A., Verma, R., Mahanti, N. (2010). Facility location selection: an interval valued intuitionistic fuzzy TOPSIS approach. Journal of Modern Mathematics and Statistics, vol. 4, no. 2, 68–72.
[18] Liu, P. (2011). An extended TOPSIS method for multiple attribute group decision making based on generalized interval-valued trapezoidal fuzzy numbers, Informatica, vol. 35, no. 2.
[19] Chi, P., Liu, P. (2013). An extended TOPSIS method for the multiple attribute decision making problems based on interval neutrosophic set. Neutrosophic Sets and Systems, vol. 1, no. 1, pp. 63–70.
[20] Liu, P., Wang, Y. (2014). Multiple attribute decision-making method based on single-valued neutrosophic normalized weighted Bonferroni mean. Neural Computing and Applications, vol. 25, no. 7-8, 2001–2010.
[21] Radulescu, C. Z., Radulescu, I. C. (2017). An extended TOPSIS approach for ranking cloud service providers, Studies in Informatics and Control, vol. 26, no. 2, pp. 183–192.
[22] Nafei, A. H., Yuan, W. Nasseri, H. (2019). Group multi-attribute decision making based on interval neutrosophic sets, Studies in Informatics and Control, vol. 28, no. 3, pp. 309–316.
[23] Ardil, C. (2023). Commercial Aircraft Selection Decision Support Model Using Fuzzy Combinative Multiple Criteria Decision Making Analysis. Journal of Sustainable Manufacturing in Transportation, 3 (2), 38-55.
[24] Ardil, C. (2023). Comparison of Composite Programming and Compromise Programming for Aircraft Selection Problem Using Multiple Criteria Decision Making Analysis Method. International Journal of Aerospace and Mechanical Engineering ,15 (11), 479-485.
[25] Ardil, C. (2023). Unmanned Aerial Vehicle Selection Using Fuzzy Multiple Criteria Decision Making Analysis. International Journal of Aerospace and Mechanical Engineering, 17 (8), 303-311.
[26] Ardil, C. (2023). Standard Fuzzy Sets for Aircraft Selection using Multiple Criteria Decision Making Analysis. International Journal of Computer and Information Engineering, 17 (4), 299-307.
[27] Ardil, C. (2023). Aircraft Selection Process Using Reference Linear Combination in Multiple Criteria Decision Making Analysis. International Journal of Aerospace and Mechanical Engineering, 17 (4), 146-155.
[28] Ardil, C. (2023). Aerial Firefighting Aircraft Selection with Standard Fuzzy Sets using Multiple Criteria Group Decision Making Analysis. International Journal of Transport and Vehicle Engineering, 17 (4), 136-145.
[29] Ardil, C. (2023). Aircraft Supplier Selection Process with Fuzzy Proximity Measure Method using Multiple Criteria Group Decision Making Analysis. International Journal of Computer and Information Engineering, 17 (4), 289-298.
[30] Ardil, C. (2023). Aircraft Supplier Selection using Multiple Criteria Group Decision Making Process with Proximity Measure Method for Determinate Fuzzy Set Ranking Analysis. International Journal of Industrial and Systems Engineering, 17 (3), 127-135.
[31] Ardil, C. (2023). Determinate Fuzzy Set Ranking Analysis for Combat Aircraft Selection with Multiple Criteria Group Decision Making. International Journal of Computer and Information Engineering, 17 (3), 272-279.
[32] Ardil, C. (2023). Using the PARIS Method for Multiple Criteria Decision Making in Unmanned Combat Aircraft Evaluation and Selection. International Journal of Aerospace and Mechanical Engineering, 17 (3), 93-103.
[33] Ardil, C. (2023). Unmanned Combat Aircraft Selection using Fuzzy Proximity Measure Method in Multiple Criteria Group Decision Making. International Journal of Computer and Systems Engineering, 17 (3), 238-245.
[34] Ardil, C. (2023). Fuzzy Multiple Criteria Decision Making for Unmanned Combat Aircraft Selection Using Proximity Measure Method. International Journal of Computer and Information Engineering, 17 (3), 193-200.
[35] Ardil, C. (2023). Composite Programming for Electric Passenger Car Selection in Multiple Criteria Decision Making. International Journal of Transport and Vehicle Engineering, 17 (2), 48-54.
[36] Ardil, C. (2023). Hospital Facility Location Selection Using Permanent Analytics Process. International Journal of Urban and Civil Engineering, 17 (1), 13-23.
[37] Ardil, C. (2022). Multiple Criteria Decision Making for Turkish AirForce Stealth Fighter Aircraft Selection. International Journal of Aerospace and Mechanical Engineering, 16 (12), 375-380.
[38] Ardil, C. (2022). Vague Multiple Criteria Decision Making Analysis Method for Fighter Aircraft Selection. International Journal of Aerospace and Mechanical Engineering, 16 (5), 133-142.
[39] Ardil, C. (2022). Aircraft Selection Problem Using Decision Uncertainty Distance in Fuzzy Multiple Criteria Decision Making Analysis. International Journal of Mechanical and Industrial Engineering ,16 (3), 57-64.
[40] Ardil, C. (2022). Fuzzy Uncertainty Theory for Stealth Fighter Aircraft Selection in Entropic Fuzzy TOPSIS Decision Analysis Process. International Journal of Aerospace and Mechanical Engineering,16 (4), 93-102.
[41] Ardil, C. (2022). Aircraft Selection Using Preference Optimization Programming (POP). International Journal of Aerospace and Mechanical Engineering, 16 (11), 292-297.
[42] Ardil, C. (2022). Fighter Aircraft Selection Using Fuzzy Preference Optimization Programming (POP). International Journal of Aerospace and Mechanical Engineering ,16 (10), 279-290.
[43] Ardil, C. (2022). Military Attack Helicopter Selection Using Distance Function Measures in Multiple Criteria Decision Making Analysis. International Journal of Aerospace and Mechanical Engineering, 16 (2), 15-22.
[44] Ardil, C. (2022). Fighter Aircraft Selection Using Neutrosophic Multiple Criteria Decision Making Analysis. International Journal of Computer and Systems Engineering ,16 (1), 5-9.
[45] Ardil, C. (2022). Neutrosophic Multiple Criteria Decision Making Analysis Method for Selecting Stealth Fighter Aircraft. International Journal of Aerospace and Mechanical Engineering ,15 (10), 466-470.
[46] Ardil, C. (2022). Fighter Aircraft Evaluation and Selection Process Based on Triangular Fuzzy Numbers in Multiple Criteria Decision Making Analysis Using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). International Journal of Computer and Systems Engineering ,15 (12), 402-408.
[47] Ardil, C. (2022). Military Combat Aircraft Selection Using Trapezoidal Fuzzy Numbers with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). International Journal of Computer and Information Engineering ,15 (12), 630-635.
[48] Ardil, C. (2021). Freighter Aircraft Selection Using Entropic Programming for Multiple Criteria Decision Making Analysis. International Journal of Mathematical and Computational Sciences, 15(12),119-136.
[49] Ardil, C. (2021). Advanced Jet Trainer and Light Attack Aircraft Selection Using Composite Programming in Multiple Criteria Decision Making Analysis Method. International Journal of Aerospace and Mechanical Engineering, 15 (12), 486-491.
[50] Ardil, C. (2021). Multiple Criteria Decision Making for Turkish Air Force Stealth Fighter Aircraft Selection. International Journal of Aerospace and Mechanical Engineering ,16 (12), 369-374.
[51] Ardil, C. (2021). Architectural acoustic modeling for predicting reverberation time in room acoustic design using multiple criteria decision making analysis. International Journal of Architectural and Environmental Engineering ,15 (9), 418-423.
[52] Ardil, C. (2021). Airline Quality Rating Using PARIS and TOPSIS in Multiple Criteria Decision Making Analysis. International Journal of Industrial and Systems Engineering ,15 (12), 516-523.
[53] Ardil, C. (2020). Software Product Quality Evaluation Model with Multiple Criteria Decision Making Analysis. International Journal of Computer and Information Engineering ,14 (12), 486-502.
[54] Ardil, C. (2020). Regional Aircraft Selection Using Preference Analysis for Reference Ideal Solution (PARIS). International Journal of Transport and Vehicle Engineering ,14 (9), 378-388.
[55] Ardil, C. (2020). A Comparative Analysis of Multiple Criteria Decision Making Analysis Methods for Strategic, Tactical, and Operational Decisions in Military Fighter Aircraft Selection. International Journal of Aerospace and Mechanical Engineering ,14 (7), 275-288.
[56] Ardil, C. (2020). Trainer Aircraft Selection Using Preference Analysis for Reference Ideal Solution (PARIS). International Journal of Aerospace and Mechanical Engineering, 14 (5), 195-208.
[57] Ardil, C. (2020). Aircraft Selection Process Using Preference Analysis for Reference Ideal Solution (PARIS). International Journal of Aerospace and Mechanical Engineering ,14 (3), 80-92.
[58] Ardil, C. (2020). Facility Location Selection using Preference Programming. International Journal of Industrial and Systems Engineering, 14 (1), 1-12.
[59] Ardil, C. (2019). Aircraft Selection Using Multiple Criteria Decision Making Analysis Method with Different Data Normalization Techniques. International Journal of Industrial and Systems Engineering ,13 (12), 744-756.
[60] Ardil, C, Pashaev, AM., Sadiqov, RA., Abdullayev, P. (2019). Multiple Criteria Decision Making Analysis for Selecting and Evaluating Fighter Aircraft. International Journal of Transport and Vehicle Engineering ,13 (11), 683-694.
[61] 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 ,13 (10), 649-657.
[62] Ardil, C. (2019). Scholar Index for Research Performance Evaluation Using Multiple Criteria Decision Making Analysis. International Journal of Educational and Pedagogical Sciences ,13 (2), 93-104.
[63] 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.