Determining attribute weights to improve solution reliability and its application to selecting leading industries

Chao Fu () and Dong-Ling Xu
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Chao Fu: Hefei University of Technology, Hefei
Dong-Ling Xu: The University of Manchester

Annals of Operations Research, 2016, vol. 245, issue 1, No 20, 426 pages

Abstract: Abstract In multiple attribute decision analysis, many methods have been proposed to determine attribute weights. However, solution reliability is rarely considered in those methods. This paper develops an objective method in the context of the evidential reasoning approach to determine attribute weights which achieve high solution reliability. Firstly, the minimal satisfaction indicator of each alternative on each attribute is constructed using the performance data of each alternative. Secondly, the concept of superior intensity of an alternative is introduced and constructed using the minimal satisfaction of each alternative. Thirdly, the concept of solution reliability on each attribute is defined as the ordered weighted averaging (OWA) of the superior intensity of each alternative. Fourthly, to calculate the solution reliability on each attribute, the methods for determining the weights of the OWA operator are developed based on the minimax disparity method. Then, each attribute weight is calculated by letting it be proportional to the solution reliability on that attribute. A problem of selecting leading industries is investigated to demonstrate the applicability and validity of the proposed method. Finally, the proposed method is compared with other four methods using the problem, which demonstrates the high solution reliability of the proposed method.

Keywords: Decision analysis; Multiple attribute decision making; Evidential reasoning; Determination of attribute weights; Solution reliability; Selecting leading industries (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s10479-014-1657-8

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