Development of a strategy for making investment decisions in the activities of machine-building enterprises in conditions of uncertainty

Investment decisions are usually made on the basis of subjective judgments of experts who are subject to information scarcity at the preliminary stages of the project. As a result, a number of mistakes are made in forecasting risks and/or making decisions, which leads to uncontrolled investments and failures of investment projects. This paper presents variable fuzzy set theory and intelligent algorithms integrated with case-based reasoning. The proposed algorithm manages numerous fuzzy concepts and variable factors of the project, as well as adjusts the decision-making process in accordance with past cases and experience. In addition, it reduces the complexity of calculations and reduces the reaction time for decision-making. Three types of risk correlations are summarized in combination with various characteristics of engineering projects in the machine-building industry, and each of these correlations is presented at the stage of making an investment decision on the project. Quantitative and qualitative theories of changing variables of fuzzy sets are also used to prevent investment risks. The approach presented in this article allows for risk analysis in a simple and intuitive way and implements the integration of objective and subjective risk assessments within the expected risk of decision makers.