In:
International Journal of Distributed Sensor Networks, SAGE Publications, Vol. 15, No. 3 ( 2019-03), p. 155014771983607-
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.
Type of Medium:
Online Resource
ISSN:
1550-1477
,
1550-1477
DOI:
10.1177/1550147719836078
Language:
English
Publisher:
SAGE Publications
Publication Date:
2019
detail.hit.zdb_id:
2192922-1
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