![Sample our Mathematics & Statistics journals, sign in here to start your FREE access for 14 days]({"type":"image" , "src" : "/sda/5943/TOC-Subject-Sample-2021-Mathematics-Statistics.jpg"})
Abstract
In [19], Liang and Wang proposed personnel selection using fuzzy MCDM algorithm. In their algorithm, they suggested a method to develop the membership function for the aggregation of the weighted ratings versus various subjective criteria of each alternative. However, despite the merits of their work, two shortcomings are found in their method:(1) The membership function of the aggregated weighted ratings of each alternative is developed based on the multiplication of the averaged ratings and the averaged weights. This is not correct because the multiplication for each weighted rating should be executed before the weighted ratings of each alternative are added. (2) Their membership function has limitations because the multiplication of two positive triangular fuzzy numbers may not produce triangular shape. Thus, their method is not reo liable. To overcome the above shortcomings. this paper presents an improved fuzzy MCDM algorithm. in which the membership function for the multiplication of two posi-tive triangular fuzzy numbers will be fully developed. A numerical example demonstrates the feasibility of the proposed method.
