Malaysian Journal of Mathematical Sciences, September 2022, Vol. 16, No. 3
A New Divergence Measure based on Fuzzy TOPSIS for Solving Staff Performance Appraisal
Saidin, M. S., Lee, L. S., Bakar, M. R. A., and Ahmad, M. Z.
Corresponding Email: lls@upm.edu.my
Received date: 23 February 2022
Accepted date: 9 August 2022
Abstract:
Various divergence measure methods have been used in many applications of fuzzy set theory
for calculating the discrimination between two objects. This paper aims to develop a novel divergence
measure incorporated with the Technique for Order of Preference by Similarity to Ideal
Solution (TOPSIS) method, along with the discussions of its properties. Since ambiguity or
uncertainty is an inevitable characteristic of multi-criteria decision-making (MCDM) problems,
the fuzzy concept is utilised to convert linguistic expressions into triangular fuzzy numbers. A
numerical example of a staff performance appraisal is given to demonstrate suggested method’s
effectiveness and practicality. Outcomes from this study were compared with various MCDM
techniques in terms of correlation coefficients and central processing unit (CPU) time. From
the results, there is a slight difference in the ranking order between the proposed method and
the other MCDM methods as all the correlation coefficient values are more than 0.9. It is also
discovered that CPU time of the proposed method is the lowest compared to the other divergence
measure techniques. Hence, the proposed method provides a more sensible and feasible
solutions than its counterparts.
Keywords: divergence measure; TOPSIS method; fuzzy concept; linguistic terms; performance appraisal
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