A Maximum Consensus Improvement Method for Group Decision Making Under Social Network with Probabilistic Linguistic Information

Group decision-making (GDM) requires consensus building, because an outcome from a consensual decision is indispensable to implement a highly acceptable solution. This paper proposes a novel consensus reaching method for GDM with Probabilistic Linguistic Term Set (PLTS) under a social network enviro...

Full description

Saved in:
Bibliographic Details
Published in:Neural processing letters 2022-02, Vol.54 (1), p.437-465
Main Authors: Hua, Zhen, Xue, Huifeng
Format: Article
Language:English
Subjects:
Artificial Intelligence
Complex Systems
Computational Intelligence
Computer Science
Decision making
Feedback
Linguistics
Novels
Optimization
Preferences
Social network analysis
Social networks
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Group decision-making (GDM) requires consensus building, because an outcome from a consensual decision is indispensable to implement a highly acceptable solution. This paper proposes a novel consensus reaching method for GDM with Probabilistic Linguistic Term Set (PLTS) under a social network environment. First, the preferences and trust evaluations of decision-makers (DMs) are collected using PLTS. Then, two types of centralities are utilized to obtain the significance of DMs, and these centralities are used to derive the group evaluation. Then, a consensus measure is employed to quantify the degree of agreement within the group. To promote further consensus, a novel feedback mechanism that combines the Identification and Direction Rule-based method with an optimization-based approach is developed to achieve maximum consensus improvement in each round of modification. Moreover, DM’s bounded rationality is factored into the GDM process for a more reliable result. Finally, illustrative examples and comparison analyses are conducted to demonstrate the effectiveness of the proposed method.
ISSN:1370-4621
1573-773X
DOI:10.1007/s11063-021-10639-y