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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 2/2019

30.06.2017 | Original Article

Prioritization of hesitant multiplicative preference relations based on data envelopment analysis for group decision making

verfasst von: Yang Lin, Ying-Ming Wang

Erschienen in: Neural Computing and Applications | Ausgabe 2/2019

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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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Metadaten
Titel
Prioritization of hesitant multiplicative preference relations based on data envelopment analysis for group decision making
verfasst von
Yang Lin
Ying-Ming Wang
Publikationsdatum
30.06.2017
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 2/2019
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-017-3075-8

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