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Granular Computing
Published in: Granular Computing 2/2021

13-08-2019 | Original Paper

Aggregation operators on cubic linguistic hesitant fuzzy numbers and their application in group decision-making

Authors: Aliya Fahmi, Saleem Abdullah, Fazli Amin

Published in: Granular Computing | Issue 2/2021

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Abstract

In this paper, we define linguistic hesitant fuzzy sets. We introduce cubic linguistic fuzzy sets and their operational laws. We propose a cubic linguistic hesitant fuzzy sets and their operational laws. We describe aggregation operators for cubic linguistic hesitant fuzzy sets which extended the generalized cubic linguistic hesitant fuzzy averaging (geometric) operator, generalized cubic linguistic hesitant fuzzy weighted averaging (GLCHFWA) operator, generalized cubic linguistic hesitant fuzzy weighted geometric (GCHFWG) operator, generalized cubic linguistic hesitant fuzzy ordered weighted average (GCLHFOWA) operator, generalized cubic linguistic hesitant fuzzy ordered weighted geometric (GCLHFOWG) operator, generalized cubic linguistic hesitant fuzzy hybrid averaging (GCLHFHA) operator and generalized cubic linguistic hesitant fuzzy hybrid geometric (GCLHFHG) operator. Moreover, we relate these aggregation operators to develop an approach to multiple-attribute group decision-making with cubic linguistic-hesitant fuzzy information. Finally, the overall ranking of an alternative is obtained. This example is presented to illustrate the feasibility and effectiveness of the proposed approach.
previous article A new approach of cubic interval-valued intuitionistic fuzzy subsemigroup and ideals
next article Multi-criteria decision making under uncertainty via the operations of generalized intuitionistic fuzzy numbers

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Metadata
Title
Aggregation operators on cubic linguistic hesitant fuzzy numbers and their application in group decision-making
Authors
Aliya Fahmi
Saleem Abdullah
Fazli Amin
Publication date
13-08-2019
Publisher
Springer International Publishing
Published in
Granular Computing / Issue 2/2021
Print ISSN: 2364-4966
Electronic ISSN: 2364-4974
DOI
https://doi.org/10.1007/s41066-019-00188-0

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