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Multi-attribute decision-making method based on Taylor expansion

Author

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  • Peng Sun
  • Jiawei Yang
  • Yongfeng Zhi

Abstract

Determining attribute weights is an indispensable step in multi-attribute decision-making problems, and it is also a top priority in the study of multi-attribute decision-making problems. Existing methods for determining attribute weights do not completely and effectively reflect the decision-maker’s dependency preferences, which will result in unreasonable ranking results for decision-makers. To solve this problem, this article proposes a feature-weighted multi-attribute decision-making method based on Taylor expansion. The method uses the natural base and the eigenvalues of the matrix to construct the feature-weighted coefficients and weights; normalizes all the feature vectors of the matrix; and constructs a new weight vector. Combined with the example to analyze and verify, the method makes reasonable use of all decision information, which saves the decision time of decision-makers.

Suggested Citation

  • Peng Sun & Jiawei Yang & Yongfeng Zhi, 2019. "Multi-attribute decision-making method based on Taylor expansion," International Journal of Distributed Sensor Networks, , vol. 15(3), pages 15501477198, March.
    • Handle: RePEc:sae:intdis:v:15:y:2019:i:3:p:1550147719836078
    DOI: 10.1177/1550147719836078
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    References listed on IDEAS

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