Abstract
Hesitant multiplicative preference relations (HMPRs) are utilized to describe situations where a decision maker gives several possible values by Saaty’s 1-9 scale in pairwise comparison. For further applications of HMPRs, this paper develops two priority methods based on data envelopment analysis (DEA) for group decision making. These methods include self-weight prioritization and the cross-weight prioritization, which are similar to the self-evaluation efficiency and the cross-evaluation efficiency in DEA theory, respectively. We prove that both of them can generate true priority weights for consistent HMPRs. The mechanisms of these proposed methods are illustrated with numerical examples. Also, comparisons with other methods are performed to show the advantages of the proposed methods.
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Acknowledgements
The authors thank Prof. Shengqun Chen for his helpful discussions and comments and also thank the anonymous referees and the editor for their insightful suggestions which lead to the present version of this paper. The work was partly supported by the National Natural Science Foundation of China (Grant No. 71371053), the Humanities and Social Sciences Foundation of Ministry of Education of China (Grant No. 16YJC630008), the Fujian Provincial Young Teacher Educational Research Foundation (Grant No. JAS160132) and the Teaching Reform Foundation of Fujian Normal University of China (Grant No. I201603023).
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Lin, Y., Wang, YM. Prioritization of hesitant multiplicative preference relations based on data envelopment analysis for group decision making. Neural Comput & Applic 31, 437–447 (2019). https://doi.org/10.1007/s00521-017-3075-8
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DOI: https://doi.org/10.1007/s00521-017-3075-8