Analytical Support for Selecting the Best Investment Project in the Presence of Fuzzy Data

The article is dedicated to the problem of optimal choice in the field of real investments in case of fuzzy estimates of financial and economic parameters. The general methodological basis of the research is an integrated approach to solving decision-making problems under conditions of uncertainty, conflict, and risk generated by them, based on the game theory, proposed by R. I. Trukhayev. In recent decades, it has been actively developed in papers by the followers of the scientific school of riskology under the leadership of V. V. Vitlinsky. One of the system-forming components of the above integration and game methodology is the classifier of information situations (there singled out seven of them). In this case, the description of possible states of the economic environment by a fuzzy set (a subset) corresponds to the seventh information situation. An attempt was made to develop a methodical apparatus for the task of selecting the best investment project from a variety of alternative projects in the presence of fuzzy data. As a result, a model based on the use of convolutions of local criteria is formulated. In accordance with the accepted methodological guidelines, the structure of the generalized (integral) indicator of the economic attractiveness (efficiency) of real investment provides for three hierarchical levels: 1) the level of detailed criteria in terms of partial criteria (financial effect, profitability, payback period), 2) the level of partial criteria, 3) the level presenting the very generalized indicator. In the basic version of the proposed model, among the possible techniques (methods) for aggregating indicators detailing the aspects of fuzzy estimates of partial criteria, the preference is given to the method by which they are joined by a combined, additive and multiplicative convolution