Model of Risk Assessment in Business Partners Selection Based on Fuzzy Logic

This paper addresses the problem of business partners’ selection under the incomplete information about companies on the market, volatile economic situation and the specific expected results expected from cooperation. During the work, we analyzed the information from the expert system of companies pre-screening, expert information and theoretical framework on statistical classification methods, methods of decision making under risk and uncertainty. Based on the information acquired, we created a model for business partners’ selection. The model takes into account the incompleteness of initial data and trying to fill it it with the help of statistical methods and fuzzy input systems. In addition, the model uses the methods of decision-making under risk for narrowing the initial set of companies and subsequent sorting it according to the cooperation principles set. The result of the model is a list of companies that are most likely to fit the terms of cooperation established by the experts.