Open Access

ARTICLE

Group Decision-Making Method with Incomplete Intuitionistic Fuzzy Preference Relations Based on a Generalized Multiplicative Consistent Concept

by Xiaoyun Lu¹, Jiuying Dong^2,3,*, Hecheng Li¹, Shuping Wan⁴

1 School of Computer Science, Qinghai Normal University, Xining, 810008, China
2 School of Science, Shanghai Institute of Technology, Shanghai, 201418, China
3 School of Statistics, Jiangxi University of Finance and Economics, Nanchang, 330013, China
4 School of Information Technology, Jiangxi University of Finance and Economics, Nanchang, 330013, China

* Corresponding Author: Jiuying Dong. Email:

(This article belongs to the Special Issue: Extension, Modeling and Applications of Fuzzy Set Theory in Engineering and Science)

Computer Modeling in Engineering & Sciences 2022, 132(3), 881-907. https://doi.org/10.32604/cmes.2022.020598

Received 02 December 2021; Accepted 26 January 2022; Issue published 27 June 2022

Abstract

Based on the analyses of existing preference group decision-making (PGDM) methods with intuitionistic fuzzy preference relations (IFPRs), we present a new PGDM framework with incomplete IFPRs. A generalized multiplicative consistent for IFPRs is defined, and a mathematical programming model is constructed to supplement the missing values in incomplete IFPRs. Moreover, in this study, another mathematical programming model is constructed to improve the consistency level of unacceptably multiplicative consistent IFPRs. For group decisionmaking (GDM) with incomplete IFPRs, three reliable sources inuencing the weights of experts are identified. Subsequently, a method for determining the weights of experts is developed by simultaneously considering three reliable sources. Furthermore, a targeted consensus process (CPR) is developed in this study with reference to the actual situation of the consensus level of each IFPR. Meanwhile, in response to the proposed multiplicative consistency definition , a novel method for determining the optimal priority weights of alternatives is redefined. Lastly, based on the above theory, a novel GDM method with incomplete IFPRs is developed, and the comparative and sensitivity analysis results demonstrate the utility and superiority of this work.

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Keywords

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