Abstract
Trapezoidal interval type-2 fuzzy soft set (TrIT2FSS) (Zhang and Zhang, Appl Math Model 37:4948–4971, 2013) is a delicious generalization of soft set theory where the performance of the alternatives over some parameters is assigned by means of trapezoidal interval type-2 fuzzy numbers (TrIT2FNs). Zhang and Zhang (2013) proposed an approach to multi-criteria group decision-making (MCGDM) problems under trapezoidal interval type-2 fuzzy soft set. However, due to the increasing complexity of decision-making problems, the performance of the alternatives may be determined randomly with respect to some possible states related to the decision-making problems which are known as stochastic multi-criteria decision-making (SMCDM) problems. To handle such type of SMCDM problems based on trapezoidal interval type-2 fuzzy soft set, no research exists till now. To fill up this lacuna, here we have formulated a new generalization of TrIT2FSS to solve the MCDM problems under stochastic environment. First, we have introduced the notion of trapezoidal interval type-2 fuzzy soft stochastic set (TrIT2FSSS). Second, we deal with the obligatory definition of expected trapezoidal interval type-2 fuzzy soft set (ETrIT2FSS). Finally, we have proposed a methodology for handling the trapezoidal interval type-2 fuzzy soft stochastic set (TrIT2FSSS) based stochastic MCDM problems. Additionally, in this model we have assumed that the weights of each of the parameters are partially known. We have proposed a process to obtain the weights of the parameters using signed distance measurement. An application of our proposed approach regarding the selection of the best company for investment of a bank has also been given to describe the feasibility and effectiveness of our proposed approach.
Similar content being viewed by others
References
Abdullah L, Adawiyah CWR, Kamal CW (2018) A decision making method based on interval type-2 fuzzy sets. An approach for ambulance location preference. Appl Comput Inform 14:65–72
Atanassov KT (1986) Intuitionistic Fuzzy Sets. Fuzzy Sets Syst 20:87–96
Basu TM, Mahapatra NK, Mondal SK (2012) A balanced solution of a fuzzy soft set based decision making problem in medical science. Appl Soft Comput 12(10):3260–3275
Cao YX, Zhou H, Wang JQ (2016) An approach to interval-valued intuitionistic stochastic multi-criteria decision-making using set pair analysis. Int J Mach Learn Cybern 9(4):629–640
Chen SM (1996) A fuzzy reasoning approach for rule-based systems based on fuzzy logics. IEEE Trans Syst Man Cybern Part B Cybern 26(5):769–778
Chen SM, Chen CD (2011) Handling forecasting problems based on high-order fuzzy logical relationships. Expert Syst Appl 38(4):3857–3864
Chen SM, Lee LW (2010a) Fuzzy multiple attributes group decision-making based on interval type-2 TOPSIS method. Expert Syst Appl 37(4):2790–2798
Chen SM, Lee LW (2010b) Fuzzy multiple criteria hierarchical group decision-making based on interval type-2 fuzzy sets. IEEE Trans Syst Man Cybern Part A Syst Hum 40(5):1120–1128
Chen SM, Lin TE, Lee LW (2014) Group decision making using incomplete fuzzy preference relations based on the additive consistency and the order consistency. Inf Sci 259:1–15
Chen SM, Wang NY, Pan JS (2009) Forecasting enrollments using automatic clustering techniques and fuzzy logical relationships. Expert Syst Appl 36(8):11070–11076
Chen TY (2013a) A linear assignment method for multiple-criteria decision analysis with interval type-2 fuzzy sets. Appl Soft Comput 13:2735–2748
Chen TY (2013b) A signed-distance-based approach to importance assessment and multi-criteria group decision analysis based on interval type-2 fuzzy set. Knowl Inf Syst 35:193–231
Chen W, Zou Y (2016) A hybrid method for rational decision making with dependence & feedback under incomplete weight information. J Comput Theor Nanosci 13(2):1236–1246
Feng F, Jun YB, Liu X, Li L (2010) An adjustable approach to fuzzy soft set based decision making. J Comput Appl Math 234:10–20
Gau W, Buehrer DJ (1993) Vague sets. IEEE Trans Syst Man Cybern 23(2):610–614
Jiang Y, Tang Y, Chen Q, Liu H, Tang J (2010) Interval-valued intuitionistic fuzzy soft sets and their properties. Comput Math Appl 60:906–918
Kallenberg O (2002) Foundations of modern probability. 2nd ed. Springer
Karnik NN, Mendel JM (2001) Operations on type-2 fuzzy sets. Fuzzy Sets Syst 122:327–348
Kong Z, Gao LQ, Wang LF (2009) Comment on a fuzzy soft set theoretic approach to decision making problems. J Comput Appl Math 223:540–542
Lee LW, Chen SM (2008) Fuzzy multiple attributes group decision-making based on the extension of TOPSIS method and interval type-2 fuzzy sets, vol 6. Proceedings of the 2008 international conference on machine learning and cybernetics, Kunming, China, pp 3260–3265
Liu K, Liu Y, Qin J (2018) An integrated ANP-VIKOR methodology for sustainable supplier selection with interval type-2 fuzzy sets. Granul Comput 3(3):193–208
Maji PK, Roy AR, Biswas R (2003) Soft set theory. Comput Math Appl 45:555–562
Majumdar P, Samanta SK (2010) Generalised fuzzy soft sets. Comput Math Appl 59(4):1425–1432
Mendel JM (2016) A comparison of three approaches for estimating (synthesizing) an interval type-2 fuzzy set model of a linguistic term for computing with words. Granul Comput 1(1):59–69
Mendel JM, John RI, Liu F (2006) Interval type-2 fuzzy logic systems made simple. IEEE Trans Fuzzy Syst 14(6):808–821
Molodtsov D (1999) Soft set theory-first results. J Comput Appl Math 37(4–5):19–31
Pawlak Z (1982) Rough sets. Int J Inform Comput Sci 11:341–356
Pedrycz W, Chen SM (2011) Granular computing and intelligent systems: design with information granules of high order and high type. Springer, Heidelberg
Pedrycz W, Chen SM (2015a) Granular computing and decision-making: interactive and iterative approaches. Springer, Heidelberg
Pedrycz W, Chen SM (2015b) Information granularity, big data, and computational intelligence. Springer, Heidelberg
Qin J (2017) Interval type-2 fuzzy Hamy mean operators and their application in multiple criteria decision making. Granul Comput 2(4):249–269
Roy AR, Maji PK (2007) A fuzzy soft set theoretic approach to decision making problems. J Fuzzy Math 203:412–418
Turksen IB (1986) Interval valued fuzzy sets based on normal forms. Fuzzy Sets Syst 20:191–210
Wang JQ, Kuang JJ, Wang J, Zhang HY (2016) An extended outranking approach to rough stochastic multi-criteria decision-making problems. Cogn Comput 8:1144–1160
Xiao Z, Xia S, Gong K, Li D (2012) The trapezoidal fuzzy soft set and its application in MCDM. Appl Math Model 36:5844–5855
Xu Z (2007) A method for multiple attribute decision making with incomplete weight information in linguistic setting. Knowl-Based Syst 20:719–725
Yang XB, Lin TY, Yang JY, Li Y, Yu D (2009) Combination of interval-valued fuzzy set and soft set. Comput Math Appl 58(3):521–527
Zadeh LA (1965) Fuzzy Sets. Inform Control 8:338–353
Zadeh LA (1975) The concept of a linguistic variable and its application to approximate reasoning-1. Inf Sci 8:199–249
Zhang Z, Zhang S (2013) A novel approach to multi attribute group decision making based on trapezoidal interval type-2 fuzzy sof sets. Appl Math Model 37:4948–4971
Zhang W, Xu Y, Wang H (2015) A consensus reaching model for 2-tuple linguistic multiple attribute group decision making with incomplete weight information. Int J Syst Sci 47(2):389–405
Zhou H, Wang JQ, Zhang HY (2017) Grey stochastic multi-criteria decision-making based on regret theory and TOPSIS, International Journal of. Mach Learn Cybern 8:651–664
Acknowledgements
The authors are very thankful to the editors and anonymous reviewers for providing very thoughtful comments which have lead to an improved version of this paper. This work is supported by the Department of Science and Technology(DST), New Delhi, India, through the letter No.DST/INSPIRE/03/2014/003326.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Manna, S., Basu, T.M. & Mondal, S.K. Trapezoidal interval type-2 fuzzy soft stochastic set and its application in stochastic multi-criteria decision-making. Granul. Comput. 4, 585–599 (2019). https://doi.org/10.1007/s41066-018-0119-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s41066-018-0119-0