Extension of the TOPSIS Method for Decision Making Problems under Complex Fuzzy Data Based on the Central Point Index - Salameh Barbat; Mahnaz Barkhordariahmadi; Vahidmomenaei Kermani (Advances in Fuzzy Systems)
This paper presents the CP-TOPSIS Model in group decision-making using complex Fuzzy Data. Complex numbers were employed in this model, and the central point index was used to define both the negative and positive ideals as well as the distance between each option. In this approach, the options are graded using complex data (due to replacing linguistic variables). One of the advantages of this model in decision-making is the capability that creates a complex fuzzy technique for investigating, grading, and selecting the best option related to complex fuzzy data. The results show that this model effectively rates and grades the complex fuzzy data through an alternative period. Quantum mechanics wave functions could not be analyzed, nor could signals or time series or stock exchange transactions predict factors of a multiperiod alternation, nor could predictions be made about any of these variables. As a result, there are numerical results in rating with high precision.