Fuzzy TOPSIS Based on α Level Set for Academic Staff Selection
Abstract
This paper applies the fuzzy TOPSIS based on α -level in solving a multi-criteria decision-making problem. The basic principle of fuzzy TOPSIS is that the chosen alternatives should have the shortest distance from the fuzzy positive ideal solution and the farthest distance from the fuzzy negative ideal solution in which can be determined by calculating the closeness coefficient. In this paper, the α-level set of the fuzzy closeness coefficient is calculated at eleven α levels. The closeness coefficient can be presented as a fuzzy number which generates a more accurate fuzzy estimation of the relative closeness. An empirical study of academic staff selection is conducted to illustrate its application.
Copyright (c) 2007 Nazirah Ramli, Nor Azizah M. Yacob
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