Fighter Aircraft Selection Using Neutrosophic Multiple Criteria Decision Making Analysis
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Fighter Aircraft Selection Using Neutrosophic Multiple Criteria Decision Making Analysis

Authors: C. Ardil

Abstract:

Fuzzy set and intuitionistic fuzzy set are dealing with the imprecision and uncertainty inherent in a complex decision problem. However, sometimes these theories are not sufficient to model indeterminate and inconsistent information encountered in real-life problems. To overcome this insufficiency, the neutrosophic set, which is useful in practical applications, is proposed, triangular neutrosophic numbers and trapezoidal neutrosophic numbers are examined, their definitions and applications are discussed. In this study, a decision making algorithm is developed using neutrosophic set processes and an application is given in fighter aircraft selection as an example of a decision making problem. The estimation of the fighter aircraft selection with the neutrosophic multiple criteria decision analysis method is examined.  

Keywords: neutrosophic set, multiple criteria decision making analysis, fighter aircraft selection, MCDMA, neutrosophic numbers

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[1] Zadeh L.A., (1965). Fuzzy Sets. Information and Control, 8, 338-353.
[2] Bellman, R.E., Zadeh, L.A. (1970). Decision-making in a fuzzy environment. Management Science, 17(4), 141–164.
[3] Smarandache, F. (1999). A Unifying Field in Logics, Neutrosophic Logic, Neutrosophy, Neutrosophic Set and Neutrosophic Probabilty. 4th (eds) American Research Press, Rehoboth, DE, USA.
[4] 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.
[5] Atanasov, K.T. (1986). Intuitionistic fuzzy sets. Fuzzy sets and systems, 20, 87-96.
[6] Atanassov, K., Gargov, G. (1989). Interval valued intuitionistic fuzzy sets.Fuzzy Sets and Systems 31(3), 343-349.
[7] Ye, J. (2014). Similarity measures between interval neutrosophic sets and their applications in multicriteria decision-making. J. Intell. Fuzzy Syst. 26, 165–172.
[8] Broumi, S., Smarandache, F., Talea, M., Bakali, A. (2016). An introduction to bipolar single valued neutrosophic graph theory. Appl. Mech. Mater., 841, 184–191.
[9] Ye, J. (2013). Multicriteria decision-making method using the correlation coefficient under single-valued neutrosophic environment. Int. J. Gen. Syst. 42, 386–394.
[10] Chakraborty, A., Mondal, S.P., Ahmadian, A., Senu, N., Alam, S., Salahshour, S. (2018). Different Forms of Triangular Neutrosophic Numbers, De-Neutrosophication Techniques, and their Applications. Symmetry 10, 327.
[11] Garg, H. (2018). New Logarithmic operational laws and their applications to multiattribute decision making for single-valued neutrosophic numbers. Cogn. Syst. Res. 52, 931–946.
[12] Wang, H., Smarandache, F., Zhang, Y., Sunderraman, R.(2010). Single valued neutrosophic sets. Multispace and Multistructure, 4, 410-413.
[13] Garg, H., Nancy (2020). Linguistic single-valued neutrosophic power aggregation operators and their applications to group decision-making problems. IEEE/CAA Journal of Automatica Sinica, 7, 546-558.
[14] Garg, H. (2019). Algorithms for possibility linguistic single-valued neutrosophic decision-making based on COPRAS and aggregation operators with new information measures. Measurement 138, 278–290.
[15] Kumar, R., Edalatpanah, S.A., Jha, S., Broumi, S., Dey, A. (2018). Neutrosophic shortest path problem. Neutrosophic Sets Syst. 23, 5–15.
[16] Edalatpanah, S.A. (2019). Nonlinear approach for neutrosophic linear programming. J. Appl. Res. Ind. Eng. 6, 367–373.
[17] Smarandache, F. (2020). The Score, Accuracy, and Certainty Functions determine a Total Order on the Set of Neutrosophic Triplets (T, I, F). Neutrosophic Sets and Systems 38 (1), 1-14.
[18] Ardil, C., Bilgen, S. (2017). Online Performance Tracking. SocioEconomic Challenges, 1(3), 58-72. ISSN (print) – 2520-6621.
[19] Ardil, C. (2018) Multidimensional Performance Tracking. International Journal of Computer and Systems Engineering, Vol:12, No:5,320-349
[20] 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.
[21] 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.
[22] Ardil, C. , Pashaev, A. , Sadiqov, R. , 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.
[23] 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.
[24] Saaty, T. L. (1990). How to make a decision: The Analytic Hierarchy Process. European Journal of Operational Research, 48(1), 9-26. doi: 10.1016/0377-2217(90)90057-I
[25] Saaty, T. L. (2008). Decision making with the analytic hierarchy process. International Journal of Services Sciences, 1(1), 83-98. doi: 10.1504/IJSSCI.2008.017590
[26] Saaty, T.L. (1980). Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation. McGraw-Hill, New York.
[27] 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.
[28] Ardil, C. (2021). 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.
[29] 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.
[30] Ardil, C. (2018) Multidimensional Compromise Programming Evaluation of Digital Commerce Websites. International Journal of Computer and Information Engineering Vol:12, No:7, 556-563.
[31] 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.
[32] Ardil, C. (2021). Freighter Aircraft Selection Using Entropic Programming for Multiple Criteria Decision Making Analysis. International Journal of Mathematical and Computational Sciences, 15(12), 125 - 132.
[33] 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.
[34] Ardil, C. (2020). Aircraft Selection Process Using Preference Analysis for Reference Ideal Solution (PARIS). International Journal of Aerospace and Mechanical Engineering, 14(3), 80 - 93.
[35] 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.
[36] Ardil, C. (2020). Trainer Aircraft Selection Using Preference Analysis for Reference Ideal Solution (PARIS). International Journal of Aerospace and Mechanical Engineering, 14(5), 195 - 209.
[37] 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.
[38] 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.
[39] Roy, B. (1991). The outranking approach and the foundation of ELECTRE methods. Theory and Decision, 31(1), 49–73.
[40] 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.
[41] Brans JP., Mareschal B. (2005). Promethee Methods. In: Multiple Criteria Decision Analysis: State of the Art Surveys. International Series in Operations Research & Management Science, vol 78, pp 163-186. Springer, New York, NY. https://doi.org/10.1007/0-387-23081-5_5.
[42] Brans, J., Ph. Vincke. (1985). A Preference Ranking Organisation Method: (The PROMETHEE Method for Multiple Criteria Decision-Making). Management Science, 31(6), 647-656.
[43] 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.
[44] 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.
[45] Ardil, C. (2020) Facility Location Selection using Preference Programming. International Journal of Industrial and Systems Engineering, 14(1), 1 - 12.
[46] Hwang, C.L.; Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications. New York: Springer-Verlag.
[47] 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.
[48] 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.
[49] 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.
[50] 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.
[51] 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.
[52] Opricovic, S. (1998). Multicriteria Optimization of Civil Engineering Systems. PhD Thesis, Faculty of Civil Engineering, Belgrade (in Serbian).
[53] Opricovic, S. (2007). A fuzzy compromise solution for multicriteria problems. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 15(3), 363–380.
[54] Opricovic, S., Tzeng, G.-H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, 156(2), 445–455.
[55] Karamaşa, Ç., Karabasevic, D., Stanujkic, D., Kookhdan, A. R., Arunodaya Raj, M., Ertürk, M. (2021). An extended single-valued neutrosophic AHP and MULTIMOORA method to evaluate the optimal training aircraft for flight training organizations.Facta Universitatis Series Mechanical Engineering, 19(3), 555 - 578.
[56] Ardil, C. (2021). 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.
[57] Ardil, C. (2021). 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.
[58] Ardil, C. (2021). Neutrosophic Multiple Criteria Decision Making Analysis Method for Selecting Stealth Fighter Aircraft. International Journal of Aerospace and Mechanical Engineering, 15(10), 459 - 463.
[59] Peng J.J., Wang J.Q., Zhang H.Y., Chen X.H., (2014). An outranking approach for multi-criteria decision-making problems with simplified neutrosophic sets, Applied Soft Computing, 25, 336-346.
[60] Ye J., (2014). A multicriteria decision-making method using aggregation operators for simplified neutrosophic sets, Journal of Intelligent and Fuzzy Systems, 26, 2459–2466.
[61] Smarandache, F.(2020). The Score, Accuracy, and Certainty Functions determine a Total Order on the Set of Neutrosophic Triplets (T, I, F). Neutrosophic Sets and Systems 38(1), 1-14.
[62] Liu P., Chu Y., Li Y., Chen Y., (2014). Some generalized neutrosophic number Hamacher aggregation operators and their application to group decision making, International Journal of Fuzzy Systems, 16(2) 242–255.