4.7 Article

An approach for multiple attribute group decision making problems with interval-valued intuitionistic trapezoidal fuzzy numbers

Journal

COMPUTERS & INDUSTRIAL ENGINEERING
Volume 66, Issue 2, Pages 311-324

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cie.2013.07.001

Keywords

Group decision making; Multiple attribute decision making; Score expected functions; Accuracy expected functions; Interval-valued intuitionistic trapezoidal fuzzy numbers; Aggregation operation

Funding

  1. National Natural Science Foundation of China (NSFC) [71101131]
  2. Chinese Ministry of Education [10YJC630277]
  3. Zhejiang Provincial National Science Foundation for Distinguished Young Scholars of China [LR13G010001]
  4. China Scholarship Council (CSC) [20115025]

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This article proposes an approach to resolve multiple attribute group decision making (MAGDM) problems with interval-valued intuitionistic trapezoidal fuzzy numbers (IVITFNs). We first introduce the cut set of IVITFNs and investigate the attitudinal score and accuracy expected functions for IVITFNs. Their novelty is that they allow the comparison of IVITFNs by taking into accounting of the experts' risk attitude. Based on these expected functions, a ranking method for IVITFNs is proposed and a ranking sensitivity analysis method with respect to the risk attitude is developed. To aggregate the information with IVITFNs, we study the desirable properties of the interval-valued intuitionistic trapezoidal fuzzy weighted geometric (IVITFWG) operator, the interval-valued intuitionistic trapezoidal fuzzy ordered weighted geometric (IVITFOWG) operator, and the interval-valued intuitionistic trapezoidal fuzzy hybrid geometric (IVITFHG) operator. It is worth noting that the aggregated value by using these operators is also an interval-valued intuitionistic trapezoidal fuzzy value. Then, based on these expected functions and aggregating operators, an approach is proposed to solve MAGDM problems in which the attribute values take the form of interval-valued intuitionistic fuzzy numbers and the expert weights take the form of real numbers. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness. (C) 2013 Elsevier Ltd. All rights reserved.

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