An Approach to Consensus Measure Based on Possibility Degrees of PLTSs in Group Decision Making

Zhao, Meng; Gao, Qian; Fang, Junyi; Xiao, Qi-rui

doi:10.1007/s40815-018-0464-9

Cited by 15 publications

(2 citation statements)

References 42 publications

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“…And for computation, the research on consistency and consensus of probabilistic linguistic preference relations can be seen in literature [50][51][52]. For PLPRs and linguistic preference relations based on discrete fuzzy numbers, both core ideas of obtaining and improving consistency and consensus are coincident.…”

Section: Comparison With the Consensus Methods Withmentioning

confidence: 99%

A Method Adjusting Consistency and Consensus for Group Decision‐Making Problems with Hesitant Fuzzy Linguistic Preference Relations Based on Discrete Fuzzy Numbers

Zhao

Liu

et al. 2018

Complexity

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In each hesitant fuzzy linguistic preference relation, experts may express their opinions through comparison linguistic information combined with a discrete fuzzy number. In this paper, a hesitant fuzzy linguistic computational model based on discrete fuzzy numbers whose support is a subset of consecutive natural numbers is proposed, which enriches the flexibility of group decision-making. First, some main concepts related to discrete fuzzy numbers and an aggregation function of individual subjective linguistic preference relations are introduced. Then, a consistency measure is presented to check and improve the consistency in a given matrix. Further, in order to achieve the predefined degree of consensus and to arrive at the final result, a consensus-reaching process based on the interactive feedback mechanism is defined. Meanwhile, a revised formula is introduced to calculate the consistency and the degree of consensus in a preference relation matrix. Besides, an illustrative example and comparative analysis are conducted through the proposed calculation process and the optimization algorithm. Finally, the analysis on the threshold values is made to help the decision-maker determine critical consensus level. The proposed method can address both consistency and consensus, and the results confirmed the effectiveness of the proposed method and its potential use in the qualitative decision-making problems.

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Section: Comparison With the Consensus Methods Withmentioning

confidence: 99%

A Method Adjusting Consistency and Consensus for Group Decision‐Making Problems with Hesitant Fuzzy Linguistic Preference Relations Based on Discrete Fuzzy Numbers

Zhao

Liu

et al. 2018

Complexity

Self Cite

View full text Add to dashboard Cite

show abstract

“…The consensus measure proves useful for reckoning the differences between experts ' preferences [19 ]. In former researches, they determined the consensus level through the distance or similarity function obtained by comparing the views of experts with other experts or the group [20]. In our research, the distance function is applied to measure consensus, the ICL of experts and GCL are calculated as follows.…”

Section: Consensus Measuresmentioning

confidence: 99%

Consensus Model of Social Network Group Decision-Making Based on Trust Relationship Among Experts and Expert Reliability

Cai

Jian

2023

J. of Syst. Eng. Electron.

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Due to people's increasing dependence on social networks, it is essential to develop a consensus model considering not only their own factors but also the interaction between people. Both external trust relationship among experts and the internal reliability of experts are important factors in decision-making. This paper focuses on improving the scientificity and effectiveness of decision-making and presents a consensus model combining trust relationship among experts and expert reliability in social network group decision-making (SN-GDM). A concept named matching degree is proposed to measure expert reliability. Meanwhile, linguistic information is applied to manage the imprecise and vague information. Matching degree is expressed by a 2-tuple linguistic model, and experts' preferences are measured by a probabilistic linguistic term set (PLTS). Subsequently, a hybrid weight is explored to weigh experts ' importance in a group. Then a consensus measure is introduced and a feedback mechanism is developed to produce some personalized recommendations with higher group consensus. Finally, a comparative example is provided to prove the scientificity and effectiveness of the proposed consensus model.

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A survey of decision-making methods with probabilistic linguistic information: bibliometrics, preliminaries, methodologies, applications and future directions

Liao

Zhang

2019

Fuzzy Optim Decis Making

160

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An Approach to Consensus Measure Based on Possibility Degrees of PLTSs in Group Decision Making

Cited by 15 publications

References 42 publications

A Method Adjusting Consistency and Consensus for Group Decision‐Making Problems with Hesitant Fuzzy Linguistic Preference Relations Based on Discrete Fuzzy Numbers

A Method Adjusting Consistency and Consensus for Group Decision‐Making Problems with Hesitant Fuzzy Linguistic Preference Relations Based on Discrete Fuzzy Numbers

Consensus Model of Social Network Group Decision-Making Based on Trust Relationship Among Experts and Expert Reliability

A survey of decision-making methods with probabilistic linguistic information: bibliometrics, preliminaries, methodologies, applications and future directions

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