This study proposes a novel fuzzy multiple-attribute group decision-making approach based on expert reliability and the evidential reasoning (ER) rule in an interval-valued intuitionistic fuzzy environment. First, to determine the reliabilities of experts, an objective method is developed by combining the similarity between the assessments provided before and after group discussion. Second, the proposed approach extends the ER rule to the case where belief degrees are intervals and employs it to combine experts’ assessments. Hereinto, several optimization models are established to produce the aggregated assessments of the alternatives. Then, the overall priority degree of each alternative can be obtained according to the aggregated assessments and further utilized to yield a ranking of alternatives. Finally, a shopping center site selection problem is analyzed by the proposed approach to demonstrate its validity and applicability.
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This research was supported by the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (No. 71521001), the National Natural Science Foundation of China (Nos. 71690235, 71601066, 71501056, 71501054, and 71303073), the Humanities and Social Science Foundation of Ministry of Education in China (Nos. 16YJA630017, 16YJA630075, 16YJC630093, and 13YJC630030), and the Foundation of North Minzu University (No. 2013XYS07).
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Ding, H., Hu, X. & Tang, X. Multiple-attribute group decision making for interval-valued intuitionistic fuzzy sets based on expert reliability and the evidential reasoning rule. Neural Comput & Applic 32, 5213–5234 (2020). https://doi.org/10.1007/s00521-019-04016-z