Z-DNMASort: A double normalization-based multiple aggregation sorting method with Z-numbers for multi-criterion sorting problems

doi:10.1016/j.ins.2023.119782

Z-DNMASort: A double normalization-based multiple aggregation sorting method with Z-numbers for multi-criterion sorting problems

2024-01-01

5

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AI

DOI：10.1016/j.ins.2023.119782

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Extensive multi-criterion sorting (MCS) methods have been developed to address problems encountered in real-world scenarios. Nevertheless, these methods did not take into account the reliability of the information given by experts, and neglected the preferences of decision-makers when calculating the comprehensive performances of alternatives. To overcome these limitations, this paper proposes a double normalization-based multiple aggregation sorting method with Z -numbers (Z-DNMASort), which can depict both the reliability and uncertainty of any available information. The method considers both quantitative and qualitative criteria in forms of benefit, cost or target types in the sorting process, and also considers the reliability of information given by experts. Furthermore, this method takes into account three aggregation techniques to reflect the preferences of decision-makers when calculating the comprehensive performances of alternatives. A case study regarding battery electric vehicle (BEV) evaluation is given to validate the proposed method. The paper concludes by providing a comprehensive analysis and discourse on the proposed method.

Keyword:

Multi-criterion sorting

Z-number

Double normalization-based multiple aggregation

Battery electric vehicle evaluation

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Z-DNMASort: A double normalization-based multiple aggregation sorting method with Z-numbers for multi-criterion sorting problems

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