4.4 Article

Managing consensus reaching process with self-confident double hierarchy linguistic preference relations in group decision making

Journal

FUZZY OPTIMIZATION AND DECISION MAKING
Volume 20, Issue 1, Pages 51-79

Publisher

SPRINGER
DOI: 10.1007/s10700-020-09331-y

Keywords

Self-confidence DHLPRs; Consensus reaching model; Priority vector; Group decision making; Simulation experiment

Funding

  1. National Natural Science Foundation of China [71771155]
  2. Project of the Key Research Institute of Humanities and Social Sciences in Sichuan colleges and Universities-Sichuan Special Education Research Center of Leshan Normal University [SCTJ-2020-B03]
  3. Fundamental Research Funds for the Central Universities of China [YJ202015, 2020ZY-SX-C01]

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This study introduces a novel preference relation model and develops a weight determining method. A consensus model is established to manage group decision making problems, and the effectiveness of the model is illustrated through case studies and simulation experiments, comparing it to other models.
Group decision making (GDM) can be defined as an environment where there exist a set of possible alternatives and a set of individuals (experts, judgements, etc.). Preference relation is one of the most widely used preference representation structures in GDM. Considering that the self-confidence degree is an important part to express preference information, and double hierarchy linguistic preference relation (DHLPR) is a cognitive complex linguistic information representation tool to express complex linguistic information, this paper presents a novel preference relation named as self-confident DHLPR. In addition, a weight-determining method is developed, which considers three kinds of information including the subjective weights and two kinds of objective weights. Furthermore, a consensus model is set up to manage the GDM problems with self-confident DHLPRs based on the priority ordering theory. The effectiveness of the proposed consensus model is illustrated by a case study concerning the selection of optimal hospitals in the field of Telemedicine. Finally, a simulation experiment is devised to testify the proposed consensus model and then some comparisons with other consensus reaching models are provided from three different angles including the number of iterations, the consensus success ratio and the distance between the original and adjusted preferences.

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