A developed Best-Worst method to solve multi-criteria decision-making problems under intuitionistic fuzzy environments

Document Type : Original Article

Author

Department of Management, Humanities College, Hazrat-e Masoumeh University, Qom, Iran

Abstract

In real-world decision-making problems, we often face multiple criteria that should be considered in the decision process. Also, the collected data are often non-crisp and reported with a degree of hesitation. In this study, using intuitionistic fuzzy numbers that can model these non-crisp and hesitant data, we propose a simple yet effective method for solving real-world multi-criteria decision-making problems. We applied our proposed approach to the intuitionistic fuzzy Best-Worst Method, which is one of the famous techniques for solving multi-criteria decision-making problems. However, the proposed method can be easily generalized to the other multi-criteria decision-making methods in intuitionistic fuzzy environments, too. Finally, the ability of the proposed approach to solve these types of problems is shown by an illustrative example.

Keywords

References

[1] L. Abdullah, N. Zulkifli, H. Liao, E. Herrera-Viedma, A. Al-Barakati, An interval-valued intuitionistic fuzzy DEMATEL method combined with choquet integral for sustainable solid waste management, Engineering Applications of Artificial Intelligence, 82 2019, 207-215.
[2] K.T. Atanassov, Intuitionistic fuzzy sets, Fuzzy sets and Systems, 20 1986, 87-96.
[3] K.T. Atanassov, Intuitionistic Fuzzy Sets: Theory and Applications, Studies in Fuzziness and Soft Computing, Berlin Heidelberg: Springer, 35 1999.
[4] J.P. Brans, Y. De Smet, PROMETHEE methods, Multiple criteria decision analysis, New York: Springer, 2016.
[5] J.P. Brans, B. Mareschal, PROMETHEE methods. Multiple criteria decision analysis: State of the art surveys, New York: Springer, 2005, 163–186.
[6] P. Burillo, H. Bustince, V. Mohedano, Some definition of intuitionistic fuzzy number, Fuzzy based expert systems, fuzzy Bulgarian enthusiasts, 1994.
[7] R. Chutia, S. Saikia, Ranking intuitionistic fuzzy numbers at levels of decision-making and its application, Expert Systems, 35(5) 2018, e12292.
[8] L. Duckstein, S. Opricovic, Multiobjective optimization in river basin development, Water resources research, 16(1) 1980, 14-20.
[9] C.L. Hwang, K.S. Yoon, Multiple Attribute Decision Making, Springer, Berlin, 1981.
[10] A. Karasan, C. Kahraman, A Novel Intuitionistic Fuzzy DEMATEL–ANP–TOPSIS Integrated Methodology for Freight Village Location Selection, Journal of Intelligent & Fuzzy Systems, 36(2) 2019, 1335-1352.
[11] V. Keršuliene, E.K. Zavadskas, Z. Turskis, Selection of rational dispute resolution method by applying new step-wise weight assessment ratio analysis (SWARA), Journal of business economics and management, 11(2) 2010, 243-258.
[12] R. Krishankumar, J. Premaladha, K.S. Ravichandran, K.R. Sekar, R. Manikandan, X.Z. Gao, A novel extension to VIKOR method under intuitionistic fuzzy context for solving personnel selection problem, Soft Computing, 24(2)2020, 1063-1081.
[13] D.F. Li, Decision and Game Theory in Management with Intuitionistic Fuzzy Sets, Studies in Fuzziness and Soft Computing, Springer-Verlag Berlin Heidelberg 2014.
[14] A.R. Mishra, R.K. Singh, D. Motwani, Intuitionistic fuzzy divergence measure-based ELECTRE method for performance of cellular mobile telephone service providers, Neural Computing and Applications, 32(8)2020, 3901-3921.
[15] S. Opricovic, Multicriteria Optimization of Civil Engineering Systems, Faculty of Civil Engineering, Belgrade, 2(1) 1998, 5–21.
[16] J. Rezaei, Best-worst multi-criteria decision-making method, Omega, 53(4) 2015, 49-57.
[17] B.D. Rouyendegh, The intuitionistic fuzzy ELECTRE model, International Journal of Management Science and Engineering Management, 13(2) 2018, 139-145.
[18] B.D. Rouyendegh, A. Yildizbasi, P. Üstünyer, Intuitionistic Fuzzy TOPSIS method for green supplier selection problem, Soft Computing, 24(3) 2020, 2215-2228.
[19] B. Roy, Classement et choix en présence de points de vue multiples. Re- vue française d’automatique, d’informatique et de recherche opérationnelle, Recherche Opérationnelle, 2(1) 1968, 57-75.
[20] T.L. Saaty, The Analytic Hierarchy Process, McGraw-Hill, New York, 1980.
[21] T.L. Saaty, How to make a decision: the analytic hierarchy process, European journal of operational research, 48(1)1990, 9-26.
[22] T.L. Saaty, What is the Analytic Hierarchy Process? In Mathematical Models for Decision Support, Springer Berlin Heidelberg, 1988.
[23] T.L. Saaty, Decision Making with Dependence and Feedback: The Analytic Network Process, RWS Publication, 1996.
[24] T.L. Saaty, Theory and Applications of the Analytic Network Process: Decision Making with Benefits, Opportunities, Costs, and Risks, RWS publications, 2005.
[25] B. Shakouri, R. Abbasi Shureshjani, B. Daneshian, F. Hosseinzadeh Lotfi, A Parametric Method for Ranking Intuitionistic Fuzzy Numbers and Its Application to Solve Intuitionistic Fuzzy Network Data Envelopment Analysis Models, Complexity, 2020 2020.
[26] X. Wang, E.E. Kerre, Reasonable properties for the ordering of fuzzy quantities (I), Fuzzy sets and systems, 118(3) 2001, 375-385.
[27] X. Wang, E.E. Kerre, Reasonable properties for the ordering of fuzzy quantities (II), Fuzzy Sets and Systems, Fuzzy sets and systems, 118(3) 2001, 387-405.
[28] H.H. Wu, Y.N. Tsai, A DEMATEL method to evaluate the causal relations among the criteria in auto spare parts industry, Applied Mathematics and Computation, 218(5) 2011, 2334-2342.
[29] M. Yamazaki, K. Ishibe, S. Yamashita, I. Miyamoto, M. Kurihara, H. Shindo, An analysis of obstructive factors to welfare service using DEMATEL method, Reports of the Faculty of Engineering, 48 1997, 25-30.
[30] K. Yoon, A reconciliation among discrete compromise solutions, Journal of the Operational Research Society, 38(3) 1987, 277-286.
Mathematics and Computational Sciences
Volume 2, Issue 3
September 2021
Pages 43-55

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History

  • Receive Date: 20 August 2021
  • Revise Date: 30 August 2021
  • Accept Date: 31 August 2021
  • First Publish Date: 31 August 2021

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