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An intuitionistic linguistic MCDM model based on probabilistic exceedance method and evidence theory

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Abstract

The optimization in multi-criteria decision making under uncertain conditions has attracted more and more scholars in recent years. However, it is still an open issue that how to better evaluate the satisfaction with more complex objects. Since the great performance of intuitionistic fuzzy set on handling the uncertain information, in this paper, a new fuzzy linguistic model for non-scalar criteria satisfaction expressed via intuitionistic fuzzy sets is proposed, which makes experts evaluate more objectively. Moreover, a corresponding aggregation approach based on the Choquet probabilistic exceedance method is also proposed. After a series of calculation processes, the final aggregated results embodied by intuitionistic fuzzy sets (IFSs) can be obtained. Then by converting them into the belief intervals, the best alternative can be selected more objectively. In addition, two real-life applications are shown to demonstrate the practicality of proposed method.

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Acknowledgments

This research is supported by the Fundamental Research Funds for the Central Universities (No. XDJK2019C085) and Chongqing Overseas Scholars Innovation Program (No. cx2018077).

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  1. School of Computer and Information Science, Southwest University, Chongqing, 400715, China

    Zeyi Liu & Fuyuan Xiao

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  1. Zeyi Liu
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Correspondence to Fuyuan Xiao.

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Liu, Z., Xiao, F. An intuitionistic linguistic MCDM model based on probabilistic exceedance method and evidence theory. Appl Intell 50, 1979–1995 (2020). https://doi.org/10.1007/s10489-020-01638-y

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