Open Access

ARTICLE

Multi-attribute Group Decision-making Based on Hesitant Bipolar-valued Fuzzy Information and Social Network

by Dhanalakshmi R¹, Sovan Samanta², Arun Kumar Sivaraman³, Jeong Gon Lee^4,*, Balasundaram A⁵, Sanamdikar Sanjay Tanaji⁶, Priya Ravindran⁷

1 Department of Computer Science and Engineering, KCG College of Technology, Chennai, 600097, Tamil Nadu, India
2 Department of Mathematics, Tamralipta Mahavidyalaya, West Bengal, 721636, India
3 School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, 600127, Tamil Nadu, India
4 Division of Applied Mathematics, Wonkwang University, Iksan-Si, Jeonbuk, 54538, Korea
5 School of Computer Science and Engineering, Center for Cyber Physical Systems, Vellore Institute of Technology, Chennai, 600127, Tamil Nadu, India
6 Department of Instrumentation Engineering, PDEAs College of Engineering, Manjari, 412307, Pune, India
7 Engineering and Research Services, HCL Technologies, Chennai, 600119, India

* Corresponding Author: Jeong Gon Lee. Email:

Computer Systems Science and Engineering 2023, 44(3), 1939-1950. https://doi.org/10.32604/csse.2023.026254

Received 20 December 2021; Accepted 27 February 2022; Issue published 01 August 2022

Abstract

Fuzzy sets have undergone several expansions and generalisations in the literature, including Atanasov’s intuitionistic fuzzy sets, type 2 fuzzy sets, and fuzzy multisets, to name a few. They can be regarded as fuzzy multisets from a formal standpoint; nevertheless, their interpretation differs from the two other approaches to fuzzy multisets that are currently available. Hesitating fuzzy sets (HFS) are very useful if consultants have hesitation in dealing with group decision-making problems between several possible memberships. However, these possible memberships can be not only crisp values in [0,1], but also interval values during a practical evaluation process. Hesitant bipolar valued fuzzy set (HBVFS) is a generalization of HFS. This paper aims to introduce a general framework of multi-attribute group decision-making using social network. We propose two types of decision-making processes: Type-1 decision-making process and Type-2 decision-making process. In the Type-1 decision-making process, the experts’ original opinion is proces for the final ranking of alternatives. In Type-2 decision making processs, there are two major aspects we consider. First, consistency tests and checking of consensus models are given for detecting that the judgments are logically rational. Otherwise, the framework demands (partial) decision-makers to review their assessments. Second, the coherence and consensus of several HBVFSs are established for final ranking of alternatives. The proposed framework is clarified by an example of software packages selection of a university.

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Keywords

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