The DOI matches its Crossref record; 69 of the 69 references it cites were found in a registry or an index.
Consensus efficiency in group decision making: A comprehensive comparative study and its optimal design
Abstract
Abstract Consensus reaching processes (CRPs) aim to help decision-makers achieve agreement regarding the solution to a common decision problem, and consequently play an increasingly important role in the resolution of group decision making (GDM) problems. To date, a large number of CRPs have been reported. However, there is a lack of a general framework and criteria to evaluate the efficiency of the different CRPs. This paper aims to fill this gap in the research literature on CRPs. To achieve this goal, firstly, a comprehensive review regarding the different approaches to CRP is reported, and a series of CRPs as the comparison objects are presented. Secondly, the following comparison criteria for measuring the efficiency of CPRs are proposed: the number of adjusted decision-makers, the number of adjusted alternatives, the number of adjusted preference values, the distance between the original and the adjusted preference information (adjustment cost), and the number of negotiation rounds required to reach consensus. Following this, a detailed simulation experiment is designed to analyze the efficiency of different CRPs under the mentioned different comparison criteria. Furthermore, new multi-stage optimization-based CRPs are also developed, which the simulation experiment shows to have better comprehensive consensus efficiency in different GDM settings.
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Cites
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Linear Diophantine fuzzy set and its applications towards multi-attribute decision-making problems
Riaz, M., & Hashmi, M. R. (2019) · Journal of Intelligent & Fuzzy Systems · doi:10.3233/jifs-190550 · Cited by 377
Zhang, H., Zhao, S., Kou, G., Li, C.-C., Dong, Y., & Herrera, F. (2020) · Information Fusion · doi:10.1016/j.inffus.2020.03.001 · Cited by 355
Self-citationSpherical Linear Diophantine Fuzzy Sets with Modeling Uncertainties in MCDM
Riaz, M., Raza Hashmi, M., Pamucar, D., & Chu, Y. (2021) · Computer Modeling in Engineering & Sciences · doi:10.32604/cmes.2021.013699 · Cited by 114
Metadata
- Authors
- Zhang, H., Dong, Y., Chiclana, F., & Yu, S.
- Venue
- European Journal of Operational Research
- Publisher
- Elsevier BV
- Published
- 2019-06
- Volume
- 275
- Issue
- 2
- Pages
- 580-598
- ISSN
- 0377-2217 (ISSN-L)
- OpenAlex
- W2901306906
- Cited by
- 339
- References
- 69
- FWCI
- 27.98
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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