A modification of technique for order preference by similarity to ideal solution (TOPSIS) through fuzzy similarity method (a numerical example of the personnel selection)

Multiple criteria decision-making (MCDM) is well known nowadays as a methodology in which a set of techniques are integrated to evaluate a set of alternatives with specified criteria for the purpose of selecting or ranking. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is well-established methodology frequently considered in MCDM analyses. TOPSIS has a sound logic that represents the rationale of human choice and is a scalar value simultaneously taking into account both the best and worst alternatives. Moreover, it has a simple computation process that could be easily programmed and finally it has the ability to rank alternatives on attributes to be visualized on a polyhedron, in at least two dimensions. Despite the advantages of this method, the process of ranking alternative according to related criteria may need more consideration. Typically, there are contributions in this article. First, a new similarity measure has been introduced followed by a modification applied to TOPSIS analyses. Second, the modified similarity technique was subsequently extended in the fuzzy context to cope with the uncertainty inherently existing in human judgments. A numerical example of the personnel selection was presented to demonstrate the possible application of the proposed method in human resource management. The outcome of applying fuzzy similarity method showed a significant distinction in ranking alternatives compered to TOPSIS method. Therefore, the modification is sound to be a proper solution.