A New Approach to Solve Group Decision Making Problems with Attribute Values and Attribute Weights Represented by Interval-Valued Intuitionistic Fuzzy Numbers

In this paper, we propose a multi-attribute group decision-making (MAGDM) method based on Dempster–Shafer Evidence Theory (DST) and linguistic intuitionistic fuzzy numbers (LIFNs), in which both the expert weights and attribute weights are unknown. Firstly, we represent LIFNs as basic probability assignments (BPAs) by DST based on linguistic scale function (LSF), and a linear programming model is proposed to combine the objective weights and subjective weights of attributes to obtain the combined weights. At the same time, the experts’ weights are obtained through Jousselme distance. Secondly, we use the weights to correct the evidence, and the comprehensive evaluation value of each alternative is calculated by the combination rule of evidence. Further, a new MAGDM approach with DST and LIFNs is presented. Finally, we give an example to explain the proposed method and compare it with other methods to show the feasibility and superiority.

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Aggregating decision information into interval-valued intuitionistic fuzzy numbers for heterogeneous multi-attribute group decision making

Knowledge-Based Systems ◽

10.1016/j.knosys.2016.09.026 ◽

2016 ◽

Vol 113 ◽

pp. 155-170 ◽

Cited By ~ 29

Author(s):

Shu-Ping Wan ◽

Jun Xu ◽

Jiu-Ying Dong

Keyword(s):

Decision Making ◽

Group Decision Making ◽

Fuzzy Numbers ◽

Group Decision ◽

Intuitionistic Fuzzy Numbers ◽

Intuitionistic Fuzzy ◽

Interval Valued

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Group Decision Making Process for Supplier Selection with TOPSIS Method under Interval-Valued Intuitionistic Fuzzy Numbers

Advances in Fuzzy Systems ◽

10.1155/2012/407942 ◽

2012 ◽

Vol 2012 ◽

pp. 1-14 ◽

Cited By ~ 24

Author(s):

Mohammad Izadikhah

Keyword(s):

Decision Making ◽

Supply Chain ◽

Group Decision Making ◽

Supplier Selection ◽

Fuzzy Numbers ◽

Group Decision ◽

Topsis Method ◽

Intuitionistic Fuzzy Numbers ◽

Intuitionistic Fuzzy ◽

Interval Valued

Supplier selection is a fundamental issue of supply chain area that heavily contributes to the overall supply chain performance, and, also, it is a hard problem since supplier selection is typically a multicriteria group decision problem. In many practical situations, there usually exists incomplete and uncertain, and the decision makers cannot easily express their judgments on the candidates with exact and crisp values. Therefore, in this paper an extended technique for order preference by similarity to ideal solution (TOPSIS) method for group decision making with Atanassov's interval-valued intuitionistic fuzzy numbers is proposed to solve the supplier selection problem under incomplete and uncertain information environment. In other researches in this area, the weights of each decision maker and in many of them the weights of criteria are predetermined, but these weights have been calculated in this paper by using the decision matrix of each decision maker. Also, the normalized Hamming distance is proposed to calculate the distance between Atanassov's interval-valued intuitionistic fuzzy numbers. Finally, a numerical example for supplier selection is given to clarify the main results developed in this paper.

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