An approach to multiple attribute group decision making based on linguistic intuitionistic fuzzy numbers
- DOI
- 10.1080/18756891.2015.1061394How to use a DOI?
- Keywords
- Linguistic intuitionistic fuzzy numbers, Fuzzy linguistic approach, Linguistic intuitionistic fuzzy aggregation operator, Multiple attribute decision making
- Abstract
Motivated by intuitionistic fuzzy sets and fzzy linguistic approach, this article proposes the concept of linguistic intuitionistic fuzzy numbers (LIFNs) where membership and and nonmembership are represented as linguistic terms. In order to process the multiple attribute decision making (MADM) with LIFNs, we introduce the linguistic score index and linguistic accuracy index of the LIFN. Simultaneously, the operation laws for LIFNs are defined and the related properties of the operation laws are studied. Further, some aggregation operators are developed, involving the linguistic intuitionistic fuzzy weighted averaging (LIFWA) operator, linguistic intuitionistic fuzzy ordered weighted averaging (LIFOWA) operator and linguistic intuitionistic fuzzy hybrid averaging (LIFHA) operator, etc., which can be utilized to aggregate preference information taking the form of LIFNs. Based on the LIFWA and the LIFHA operators, we propose an approach to handle MADM under LIFNs environment. Finally, an illustrative example is given to verify the feasibility and effectiveness of the proposed method, which are then compared to other representative methods.
- Copyright
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Zichun Chen AU - Penghui Liu AU - Zheng Pei PY - 2015 DA - 2015/08/01 TI - An approach to multiple attribute group decision making based on linguistic intuitionistic fuzzy numbers JO - International Journal of Computational Intelligence Systems SP - 747 EP - 760 VL - 8 IS - 4 SN - 1875-6883 UR - https://doi.org/10.1080/18756891.2015.1061394 DO - 10.1080/18756891.2015.1061394 ID - Chen2015 ER -