Evaluation of Salesperson Candidate’s with Fuzzy TOPSIS

Because of the heavy competition and uncertainty in market conditions, attainment of complete and certain information flow becomes harder for businesses. In such environments, decision making with fuzzy data is rather important. Problems’ structures in practice are usually complicated and they include more than one criterias and alternatives. The aim of this study is to investigate the applicability of Fuzzy TOPSIS (Technique For Order Performance By Similarity To Ideal Solution) Algorithm for salesperson selection in fuzzy environments where linguistic uncertainty exist. In fuzzy environments, operations with imprecise data are so important in terms of decision making. Fuzzy TOPSIS Algorithm is a multiple criteria decision making tool. This method supports group decision making and evaluation of quantitative and qualitative criterias simultaneously. In the study, a firm’s salesperson selection process is analyzed. This firm has 17 sale stores with high, medium and low concept levels in Turkey’s various regions. Trapezoidal fuzzy numbers used for more sensitive decision making. This study represented that Fuzzy TOPSIS Algorithm is efficiently applicable for salesperson selection in a Fuzzy Multiple Criteria Decision Making Problem.