4.3 Article

The linguistic intuitionistic fuzzy set TOPSIS method for linguistic multi-criteria decision makings

Journal

Publisher

ATLANTIS PRESS
DOI: 10.2991/ijcis.11.1.10

Keywords

The TOPSIS method; The 2-tuple linguistic model; Hesitant fuzzy linguistic term set; Intuitionistic fuzzy sets; Linguistic multi-criteria decision makings

Funding

  1. National Natural Science Foundation of China [61372187]
  2. scientific and technological project of Sichuan Province [2016GZ0099]
  3. open research fund of key laboratory of intelligent network information processing, Xihua University [szjj2014-052, szjj2015-061]

Ask authors/readers for more resources

In the paper, we express uncertain assessments information in linguistic multi-criteria decision makings (LMCDMs) as linguistic intuitionistic fuzzy sets, i.e., the decision maker provides membership and non-membership fuzzy linguistic terms to represent uncertain assessments information of alternatives in LMCDMs, and present Hamming distance between two linguistic intuitionistic fuzzy sets. Then we propose the linguistic intuitionistic fuzzy set TOPSIS method for LMCDMs, compared with the traditional TOPSIS method, we provide different the positive ideal solution, the negative ideal solution and the relative closeness degrees of alternatives, in addition, we design an algorithm to finish the linguistic intuitionistic fuzzy set TOPSIS method for LMCDMs. We utilize a LMCDM problem to illustrate the performance, usefulness and effectiveness of the linguistic intuitionistic fuzzy set TOPSIS method, and compare it with the hesitant fuzzy linguistic multi-criteria optimization and compromise solution (HFL-VIKOR) method, the symbolic aggregation-based method and the hesitant fuzzy linguistic TOPSIS (HFL-TOPSIS) method in the example, results show that the linguistic intuitionistic fuzzy set TOPSIS method is a useful and alternative method for LMCDMs.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.3
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available