Fuzzy multiple attributes group decision-making based on the extension of TOPSIS method and interval type-2 fuzzy sets

Published 1 July 2008

Li-Wei Lee, Shyi‐Ming Chen

DOI10.1109/icmlc.2008.4620968

Citations131

TL;DR

The TOPSIS method is extended to propose a new method for handling fuzzy multiple attributes group decision-making problems based on the ranking values of interval type-2 fuzzy sets, which provides a useful way to handle fuzzy multiple attribute group decisions in a more flexible and more intelligent manner.

Abstract

Type-2 fuzzy sets involve more uncertainties than type-1 fuzzy sets. They provide us additional degrees of freedom to represent the uncertainty and the fuzziness of the real-world. Type-2 fuzzy sets can be regarded as an extension of type-1 fuzzy sets. In this paper, we extend the TOPSIS method to propose a new method for handling fuzzy multiple attributes group decision-making problems based on the ranking values of interval type-2 fuzzy sets. The proposed method provides us a useful way to handle fuzzy multiple attributes group decision-making problems in a more flexible and more intelligent manner.

Keywords

Computer ScienceDecision Sciences

Information and ControlFuzzy sets

66,132 Citations1965L. A. Zadeh

Lecture notes in economics and mathematical systemsMultiple Attribute Decision Making

8,145 Citations1981Ching-Lai Hwang, Kwangsun Yoon

View PDF

Fuzzy Sets and SystemsExtensions of the TOPSIS for group decision-making under fuzzy environment

3,682 Citations2000Chen‐Tung Arthur Chen

The rating of each alternative and the weight of each criterion are described by linguistic terms which can be expressed in triangular fuzzy numbers and a vertex method is proposed to calculate the distance between two triangular fuzzyNumbers.

IEEE Transactions on Fuzzy SystemsInterval Type-2 Fuzzy Logic Systems Made Simple

2,062 Citations2006Jerry M. Mendel, Robert John +1 more

This paper demonstrates that it is unnecessary to take the route from general T2 FS to IT2 FS, and that all of the results that are needed to implement an IT2 FLS can be obtained using T1 FS mathematics.

Fuzzy Sets and SystemsThe maximizing deviation method for group multiple attribute decision making under linguistic environment

253 Citations2007Zhibin Wu, Yihua Chen

A method for multi-attribute decision making problems with linguistic information, in which the preference values take the form of linguistic variables, and a procedure to group multiple attribute decision making is provided under linguistic environment.

A new method for fuzzy multiple attributes group decision-making based on the arithmetic operations of interval type-2 fuzzy sets

51 Citations2008Li-Wei Lee, Shyi‐Ming Chen

The proposed method provides a useful way to handle fuzzy multiple attributes group decision-making problems in a more flexible and more intelligent manner due to the fact that it uses interval type-2 fuzzy sets rather than traditional type-1 fuzzy sets to represent the evaluating values and the weights of attributes.

Fuzzy Sets and SystemsA method for fuzzy aggregation based on group expert evaluations

42 Citations2005Teimuraz Tsabadze

An approach to group decision-making based on the coordination index and similarity of the finite collections of fuzzy sets and a specific kind of fuzzy aggregation operator is proposed.

Lecture notes in computer scienceFuzzy Interpolative Reasoning Using Interval Type-2 Fuzzy Sets

23 Citations2008Li‐Wei Lee, Shyi‐Ming Chen

This paper calculates the ranking values through the reference points and the heights of the upper and the lower membership functions of interval type-2 fuzzy sets to handle fuzzy interpolative reasoning in sparse fuzzy rule-based system in a more flexible manner.