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The group consensus based evidential reasoning approach for multiple attributive group decision analysis

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  • Fu, Chao
  • Yang, Shan-Lin

Abstract

Many multiple attribute decision analysis problems include both quantitative and qualitative attributes with various kinds of uncertainties such as ignorance, fuzziness, interval data, and interval belief degrees. An evidential reasoning (ER) approach developed in the 1990s and in recent years can be used to model these problems. In this paper, the ER approach is extended to group consensus (GC) situations for multiple attributive group decision analysis problems. In order to construct and check the GC, a compatibility measure between two belief structures is developed first. Considering two experts' utilities, the compatibility between their assessments is naturally constructed using the compatibility measure. Based on the compatibility between two experts' assessments, the GC at a specific level that may be the attribute level, the alternative level, or the global level, can be constructed and reached after the group analysis and discussion within specified times. Under the condition of GC, we conduct a study on the forming of group assessments for alternatives, the achievement of the aggregated utilities of assessment grades, and the properties and procedure of the extended ER approach. An engineering project management software selection problem is solved by the extended ER approach to demonstrate its detailed implementation process, and its validity and applicability.

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  • Fu, Chao & Yang, Shan-Lin, 2010. "The group consensus based evidential reasoning approach for multiple attributive group decision analysis," European Journal of Operational Research, Elsevier, vol. 206(3), pages 601-608, November.
  • Handle: RePEc:eee:ejores:v:206:y:2010:i:3:p:601-608
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    Cited by:

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    7. González-Arteaga, T. & Alcantud, J.C.R. & de Andrés Calle, R., 2016. "A cardinal dissensus measure based on the Mahalanobis distance," European Journal of Operational Research, Elsevier, vol. 251(2), pages 575-585.
    8. Liu, Jiapeng & Liao, Xiuwu & Yang, Jian-bo, 2015. "A group decision-making approach based on evidential reasoning for multiple criteria sorting problem with uncertainty," European Journal of Operational Research, Elsevier, vol. 246(3), pages 858-873.
    9. Xue, Min & Fu, Chao & Yang, Shan-Lin, 2020. "Group consensus reaching based on a combination of expert weight and expert reliability," Applied Mathematics and Computation, Elsevier, vol. 369(C).
    10. Qiang Yang & Ping-an Du & Yong Wang & Bin Liang, 2017. "A rough set approach for determining weights of decision makers in group decision making," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-16, February.
    11. Min Xue & Chao Fu & Shan-Lin Yang, 2021. "Dynamic Expert Reliability Based Feedback Mechanism in Consensus Reaching Process with Distributed Preference Relations," Group Decision and Negotiation, Springer, vol. 30(2), pages 341-375, April.
    12. Shenghai Zhou & Xuanhua Xu & Yanju Zhou & Xiaohong Chen, 2017. "A Large Group Decision-Making Method Based on Fuzzy Preference Relation," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(03), pages 881-897, May.
    13. Fu, Chao & Yang, Shanlin, 2011. "An attribute weight based feedback model for multiple attributive group decision analysis problems with group consensus requirements in evidential reasoning context," European Journal of Operational Research, Elsevier, vol. 212(1), pages 179-189, July.
    14. Dong, Qingxing & Cooper, Orrin, 2016. "A peer-to-peer dynamic adaptive consensus reaching model for the group AHP decision making," European Journal of Operational Research, Elsevier, vol. 250(2), pages 521-530.
    15. Dong-Ling Xu, 2012. "An introduction and survey of the evidential reasoning approach for multiple criteria decision analysis," Annals of Operations Research, Springer, vol. 195(1), pages 163-187, May.
    16. Yin Liu & Wenjun Chang & Xuefei Jia, 2023. "A Group Consensus Model for Multiple Attributes Group Decision Making with Interval Belief Distribution and Interval Distributed Preference Relation," Group Decision and Negotiation, Springer, vol. 32(3), pages 701-727, June.
    17. Fu, Chao & Yang, Jian-Bo & Yang, Shan-Lin, 2015. "A group evidential reasoning approach based on expert reliability," European Journal of Operational Research, Elsevier, vol. 246(3), pages 886-893.
    18. Gong, Zaiwu & Zhang, Huanhuan & Forrest, Jeffrey & Li, Lianshui & Xu, Xiaoxia, 2015. "Two consensus models based on the minimum cost and maximum return regarding either all individuals or one individual," European Journal of Operational Research, Elsevier, vol. 240(1), pages 183-192.
    19. Huang, Yeu-Shiang & Chang, Wei-Chen & Li, Wei-Hao & Lin, Zu-Liang, 2013. "Aggregation of utility-based individual preferences for group decision-making," European Journal of Operational Research, Elsevier, vol. 229(2), pages 462-469.
    20. Fu, Chao & Yang, Shanlin, 2012. "An evidential reasoning based consensus model for multiple attribute group decision analysis problems with interval-valued group consensus requirements," European Journal of Operational Research, Elsevier, vol. 223(1), pages 167-176.
    21. Fu, Chao & Chang, Wenjun & Xue, Min & Yang, Shanlin, 2019. "Multiple criteria group decision making with belief distributions and distributed preference relations," European Journal of Operational Research, Elsevier, vol. 273(2), pages 623-633.
    22. Yong Liu & Ting Zhou & Jeffrey Yi-Lin Forrest, 2020. "A Multivariate Minimum Cost Consensus Model for Negotiations of Holdout Demolition," Group Decision and Negotiation, Springer, vol. 29(5), pages 871-899, October.
    23. Wenjun Chang & Chao Fu & Nanping Feng & Shanlin Yang, 2021. "Multi-criteria Group Decision Making with Various Ordinal Assessments," Group Decision and Negotiation, Springer, vol. 30(6), pages 1285-1314, December.

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