| Autor: |
Yueqin Gu, Tiantian Hao, Dong Cheng, Juan Wang, Faxin Cheng |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
International Journal of Computational Intelligence Systems, Vol 14, Iss 1 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
1875-6883 |
| DOI: |
10.2991/ijcis.d.201228.001 |
| Popis: |
In social network group decision-making, adjusting the opinions of decision makers is often used to promote consensus. But decision makers are not always willing to accept the feedback mechanism, and decision-makers' trust relationships are not constant during the consensus process. This paper constructs a novel consensus model with double feedback mechanism based on dynamic relationship to solve social network group decision-making problems. It overcomes the deficiency of single feedback mechanism and improves consensus degrees. This double feedback mechanism comprises a weight feedback mechanism and an alternative-contents feedback mechanism. In each round of this double feedback mechanism, the trust relationships between decision makers are dynamic, the trust scores are adjusted to update the weights of decision makers on the basis of the weight feedback mechanism. Synchronously, adjust the contents of alternatives with low dominance degree according to the alternative-contents feedback mechanism, which can change the evaluation opinions of the decision makers. Moreover, an example of a decision-making problem about a Public-Private-Partnership construction project illustrates the feasibility and validity of the proposed method. Finally, the comparisons between this paper and existing studies help point out the advantages of the proposed methods which can improve decision makers' consensus degrees and satisfaction with alternatives. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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