Multi-attribute decision-making method based on Taylor expansion

• Published in: International journal of distributed sensor networks Vol. 15; no. 3; p. 155014771983607
• Main Authors: Sun, Peng, Yang, Jiawei, Zhi, Yongfeng
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.03.2019; Wiley
• Subjects: analytic hierarchy process; feature weighting; Taylor expands; Multi-attribute decision-making
• ISSN: 1550-1329; 1550-1477; 1550-1477
• DOI: 10.1177/1550147719836078

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.