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2023 | OriginalPaper | Buchkapitel

5. A Hesitant Multiplicative Best-Worst Method for Multiple Criteria Decision-Making

verfasst von : Yejun Xu, Dayong Wang

Erschienen in: Advances in Best-Worst Method

Verlag: Springer Nature Switzerland

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Abstract

The classical Best-Worst Method (BWM) and its expansion form in the multiple criteria decision-making problem under different backgrounds are widely used to calculate the weights of criteria. The traditional BWM uses the accurate value based on Saaty’s scale to describe a decision maker (DM)’s preferences. However, a DM may be unsure about his preference and may give several possible values to express his preferences. In this situation, the hesitant multiplicative elements may be truly reflected the DM’s preference relation. This paper incorporates the BWM, the hesitant multiplicative preference relations (HMPR), and proposes HMBWM. Three different models are proposed to determine the weights from hesitant multiplicative best-to-others (HMBO) and hesitant multiplicative others-to-worst (HMOW) vectors. Finally, a case study of choosing commercial endowment insurance products is constructed to illustrate the practicality and correctness of the proposed model.

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Metadaten
Titel
A Hesitant Multiplicative Best-Worst Method for Multiple Criteria Decision-Making
verfasst von
Yejun Xu
Dayong Wang
Copyright-Jahr
2023
DOI
https://doi.org/10.1007/978-3-031-40328-6_5

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