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A group decision-making approach based on evidential reasoning for multiple criteria sorting problem with uncertainty

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  • Liu, Jiapeng
  • Liao, Xiuwu
  • Yang, Jian-bo

Abstract

A new group decision-making approach is developed to address a multiple criteria sorting problem with uncertainty. The uncertainty in this paper refers to imprecise evaluations of alternatives with respect to the considered criteria. The belief structure and the evidential reasoning approach are employed to represent and aggregate the uncertain evaluations. In our approach, the preference information elicited from a group of decision makers is composed of the assignment examples of some reference alternatives. The disaggregation–aggregation paradigm is utilized to infer compatible preference models from these assignment examples. To help the group reach an agreement on the assignment of alternatives, we propose a consensus-reaching process. In this process, a consensus degree is defined to measure the agreement among the decision makers’ opinions. When the decision makers are not satisfied with the consensus degree, possible solutions are explored to help them adjust assignment examples in order to improve the consensus level. If the consensus degree arrives at a satisfactory level, a linear program is built to determine the collective assignment of alternatives. The application of the proposed approach to a customer satisfaction analysis is presented at the end of the paper.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ejores:v:246:y:2015:i:3:p:858-873
    DOI: 10.1016/j.ejor.2015.05.027
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    2. Wu, Siqi & Wu, Meng & Dong, Yucheng & Liang, Haiming & Zhao, Sihai, 2020. "The 2-rank additive model with axiomatic design in multiple attribute decision making," European Journal of Operational Research, Elsevier, vol. 287(2), pages 536-545.
    3. Wu, Xingli & Liao, Huchang, 2023. "Value-driven preference disaggregation analysis for uncertain preference information," Omega, Elsevier, vol. 115(C).
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    6. Galo, Nadya Regina & Calache, Lucas Daniel Del Rosso & Carpinetti, Luiz Cesar Ribeiro, 2018. "A group decision approach for supplier categorization based on hesitant fuzzy and ELECTRE TRI," International Journal of Production Economics, Elsevier, vol. 202(C), pages 182-196.
    7. Jindong Qin & Yingying Liang & Luis Martinez & Alessio Ishizaka & Witold Pedrycz, 2023. "ORESTE-SORT: a novel multiple criteria sorting method for sorting port group competitiveness," Annals of Operations Research, Springer, vol. 325(2), pages 875-909, June.
    8. Ru, Zice & Liu, Jiapeng & Kadziński, Miłosz & Liao, Xiuwu, 2023. "Probabilistic ordinal regression methods for multiple criteria sorting admitting certain and uncertain preferences," European Journal of Operational Research, Elsevier, vol. 311(2), pages 596-616.
    9. 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.
    10. Miłosz Kadziński & Lucia Rocchi & Grzegorz Miebs & David Grohmann & Maria Elena Menconi & Luisa Paolotti, 2018. "Multiple Criteria Assessment of Insulating Materials with a Group Decision Framework Incorporating Outranking Preference Model and Characteristic Class Profiles," Group Decision and Negotiation, Springer, vol. 27(1), pages 33-59, February.
    11. Wang, Liang & Zhang, Zi-Xin & Ishizaka, Alessio & Wang, Ying-Ming & Martínez, Luis, 2023. "TODIMSort: A TODIM based method for sorting problems," Omega, Elsevier, vol. 115(C).
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