IMPROVEMENT OF THE SIMULATION MODEL IN THE MANAGEMENT DECISION SUPPORT SYSTEM AT SMALL BUSINESS ENTERPRISES

Abstract

The article shows that the process of strategic management in small enterprises is informal and is mainly based on the manager's knowledge among other tasks. Emphasis is placed on the relevance of the task of creating an information system for decision management, which, based on the planning of the financial state of a small enterprise, should help the manager to rationally allocate financial resources. A new approach to solving this task has been developed through the creation of mechanisms and tools to support the process of making investment decisions in small businesses, using the procedure of situational analysis of the market as a complex socioeconomic system in conditions of uncertainty. The simulation model of the management system is presented, considered as a key element of the decision support system, which determines the effectiveness of decisions. The study is based on the integration of the paradigm of multi-agent systems as a model of the control system, built with the help of inductive judgments of agents and tools of fuzzy logical inference for processing uncertain information. It was analyzed that in the framework of creating such information products, it is advisable to take into account the use of elements of socialization of business processes to create applications that would be not only convenient, but also effective tools. In addition, based on the accumulation and analysis of data from statistical databases, the system should be able to conduct a comprehensive analysis of the industry, which expands the opportunities for decision-making by potential investors and managers. It is indicated that the proposed approach increases the justification of applied management decisions based on the methodology of multi-agent programming, procedures of fuzzy logical conclusion and decision-making in conditions of uncertainty. The results confirm the use of fuzzy logic methods for processing fuzzy information and forming fuzzy logical conclusions in a decision support system, which makes it promising for evaluating situational strategies and developing effective management solutions.