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An interval-valued Pythagorean prioritized operator-based game theoretical framework with its applications in multicriteria group decision making

Citation

Han, Y and Deng, Y and Cao, Z and Lin, C-T, An interval-valued Pythagorean prioritized operator-based game theoretical framework with its applications in multicriteria group decision making, Neural Computing and Applications pp. 1-19. ISSN 0941-0643 (2019) [Refereed Article]

Copyright Statement

Copyright 2019 Springer-Verlag London Ltd., part of Springer Nature

DOI: doi:10.1007/s00521-019-04014-1

Abstract

Multicriteria decision-making process explicitly evaluates multiple conflicting criteria in decision making. The conventional decision-making approaches assumed that each agent is independent, but the reality is that each agent aims to maximize personal benefit which causes a negative influence on other agents' behaviors in a real-world competitive environment. In our study, we proposed an interval-valued Pythagorean prioritized operator-based game theoretical framework to mitigate the cross-influence problem. The proposed framework considers both prioritized levels among various criteria and decision makers within five stages. Notably, the interval-valued Pythagorean fuzzy sets are supposed to express the uncertainty of experts, and the game theories are applied to optimize the combination of strategies in interactive situations. Additionally, we also provided illustrative examples to address the application of our proposed framework. In summary, we provided a human-inspired framework to represent the behavior of group decision making in the interactive environment, which is potential to simulate the process of realistic humans thinking.

Item Details

Item Type:Refereed Article
Keywords:interval-valued Pythagorean fuzzy sets, game theory, multicriteria group decision making, priority level, fuzzy sets and intelligence
Research Division:Information and Computing Sciences
Research Group:Artificial Intelligence and Image Processing
Research Field:Neural, Evolutionary and Fuzzy Computation
Objective Division:Defence
Objective Group:Defence
Objective Field:Intelligence
UTAS Author:Cao, Z (Mr Zehong Cao)
ID Code:131258
Year Published:2019
Web of Science® Times Cited:4
Deposited By:Information and Communication Technology
Deposited On:2019-03-09
Last Modified:2019-05-13
Downloads:0

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