Journal
IEEE TRANSACTIONS ON CYBERNETICS
Volume 51, Issue 1, Pages 283-296Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCYB.2020.2985069
Keywords
Linguistics; Decision making; Tools; Semantics; Analytical models; Computational modeling; Double hierarchy linguistic preference relation; consensus model; large-scale group decision-making; minority opinions; noncooperative behaviors
Categories
Funding
- National Natural Science Foundation of China [71771155, 71771156]
- Fundamental Research Funds for the Central Universities [YJ202015, SXYPY202038]
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This article explores the management of minority opinions and noncooperative behaviors in large-scale group decision-making, proposing a consensus model and developing corresponding basic tools. Through a practical case study, it demonstrates the feasibility and effectiveness of the consensus model.
With the rapid development of society and continual progress of science and technology, large-scale group decision-making (LSGDM) problems are very commonly encountered in real-life situations. Considering that the information required for decision-making and people's cognition processes is becoming more and more complex, double hierarchy linguistic preference relation (DHLPR) can be used to express complex linguistic information reasonably and intuitively. Sometimes experts in LSGDM unwillingly modify their preferences or even modify them on purpose in a contrary way to the other experts. Thus, differing opinions or minority preferences are often referred to as obstacles to decision-making. This article develops a consensus model to manage minority opinions and noncooperative behaviors in LSGDM with DHLPRs. In addition, to establish the consensus model, some basic tools, such as the clustering method, weights-determining method, and adjustment coefficients-determining method, are developed. Finally, a practical LSGDM problem is set up to prove that the proposed consensus model is feasible and effective, and some comparative analyses are made to highlight the advantages of these methods and models, as well as to analyze current deficiencies.
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