Grey best-worst method for multiple experts multiple criteria decision making under uncertainty
Date
2020Author
Mahmoudi, Amin
Mi, Xiaomei
Liao, Huchang
Feylizadeh, Mohammad Reza
Turskis, Zenonas
Metadata
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In practice, the judgments of decision-makers are often uncertain and thus cannot be represented by accurate values. In this study, the opinions of decision-makers are collected based on grey linguistic variables and the data retains the grey nature throughout all the decision-making process. A grey best-worst method (GBWM) is developed for multiple experts multiple criteria decision-making problems that can employ grey linguistic variables as input data to cover uncertainty. An example is solved by the GBWM and then a sensitivity analysis is done to show the robustness of the method. Comparative analyses verify the validity and advantages of the GBWM.