Consensus Reaching Model for 2-Rank Group Decision Making with Personalized Individual Semantics

Traditional group decision-making problems focus on obtaining a complete ranking of all alternatives from best to worst. However, in many real-life scenarios, there are instances where it is necessary to assign only two rank levels to alternatives, creating a ranking where one subset of alternatives is prioritized above another subset. These scenarios are referred to as 2-rank group decision-making problems. Linguistic preference relations serve as an effective tool for expressing decision-makers preferences, as they allow comparisons between two alternatives at a time using linguistic terms. Nonetheless, in 2-rank group decision-making problems with linguistic preference relations, it is common for the same linguistic term to hold different meanings for different decision-makers, a phenomenon known as personalized individual semantics (PISs). Addressing how to model PISs in 2-rank group decision-making problems presents a significant challenge. In this paper, we develop a consensus-reaching model for 2-rank linguistic group decision-making problems, incorporating PISs and consistency control for decision-makers. Specifically, we first employ consistency-driven models to evaluate and improve the consistency of each decision-makers linguistic preference relations. Based on this foundation, we determine the 2-rank preference vectors for both individuals and the group. Subsequently, we propose a 2-rank consensus measurement method and design a 2-rank consensus-reaching process to help decision-makers enhance their consensus level. This involves the development of a PIS-based consensus level maximization model and a PIS-based minimum adjustment model. Furthermore, we introduce an algorithm to implement the consensus-reaching framework. Ultimately, numerical experiments and simulation results are provided to demonstrate the effectiveness of the proposed method.

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Published
2024-10-06
DOI
https://doi.org/10.1109/smc54092.2024.10831540
Primary Topic
Multi-Criteria Decision Making
Type
article
Field-Weighted Citation Impact
0.00

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article

Consensus Reaching Model for 2-Rank Group Decision Making with Personalized Individual Semantics

Wenyu Yu, Zheng Zhang, Ke Li
Multi-Criteria Decision Making
article

Consensus Reaching Model for 2-Rank Group Decision Making with Personalized Individual Semantics

Wenyu Yu, Zheng Zhang, Ke Li
article en

Abstract

Traditional group decision-making problems focus on obtaining a complete ranking of all alternatives from best to worst. However, in many real-life scenarios, there are instances where it is necessary to assign only two rank levels to alternatives, creating a ranking where one subset of alternatives is prioritized above another subset. These scenarios are referred to as 2-rank group decision-making problems. Linguistic preference relations serve as an effective tool for expressing decision-makers preferences, as they allow comparisons between two alternatives at a time using linguistic terms. Nonetheless, in 2-rank group decision-making problems with linguistic preference relations, it is common for the same linguistic term to hold different meanings for different decision-makers, a phenomenon known as personalized individual semantics (PISs). Addressing how to model PISs in 2-rank group decision-making problems presents a significant challenge. In this paper, we develop a consensus-reaching model for 2-rank linguistic group decision-making problems, incorporating PISs and consistency control for decision-makers. Specifically, we first employ consistency-driven models to evaluate and improve the consistency of each decision-makers linguistic preference relations. Based on this foundation, we determine the 2-rank preference vectors for both individuals and the group. Subsequently, we propose a 2-rank consensus measurement method and design a 2-rank consensus-reaching process to help decision-makers enhance their consensus level. This involves the development of a PIS-based consensus level maximization model and a PIS-based minimum adjustment model. Furthermore, we introduce an algorithm to implement the consensus-reaching framework. Ultimately, numerical experiments and simulation results are provided to demonstrate the effectiveness of the proposed method.

Dongbei University of Finance and Economics (CN), Sichuan University (CN), Dalian University of Technology (CN)
National Natural Science Foundation of China, Ministry of Education of the People's Republic of China, Fundamental Research Funds for the Central Universities
Peace, Justice and strong institutions
Openalex Percentile: Top 68%
Multi-Criteria Decision Making
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