Multi-attribute decision-making method based on Taylor expansion

Peng Sun, Jiawei Yang and Yongfeng Zhi

International Journal of Distributed Sensor Networks, 2019, vol. 15, issue 3, 1550147719836078

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.

Keywords: Multi-attribute decision-making; analytic hierarchy process; Taylor expands; feature weighting (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:15:y:2019:i:3:p:1550147719836078

DOI: 10.1177/1550147719836078

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