Accuracy of the TOPSIS method with different input data

Using fuzzy logic in multi-criteria problems allows real-world problems to be modeled with greater accuracy. In addition, it is possible to solve problems in which all data are incomplete. The difficulty may be the choice of an appropriate technique leading to a ranking calculation. Methods fully integrated with fuzzy logic can be used. It is also possible to convert fuzzy data to crisp values and then apply traditional MCDA methods. In this paper, the performance of the TOPSIS method in a crisp and fuzzy environment was analyzed. The approaches of operating fully on uncertain data when calculating preference values were compared with converting data to crisp values using selected membership functions. The research has shown that significant differences and discrepancies in how the alternatives are classified are noticeable in the rankings.