Simulation Modeling as a Tool for Resource Management in Conditions of Information Uncertainty

Introduction. The article proposes the use of the probabilistic-automaton modeling method to optimize the allocation of financial resources from the Compulsory State Social Insurance Fund for Unemployment (hereinafter referred to as the Fund). This approach aims to increase funding in favor of active labor market policy measures. Objective. The purpose of the proposed methods is to identify approaches that, under conditions of macroeco-nomic decline, enable the exploration of financial support scenarios for the national labor market. By optimally utilizing resources, this would contribute to restoring its relative structural balance. Results. To define the studied processes as mechanisms of transition from one state to another, financial flows are simulated using a system of probabilistic automata. These automata are interconnected by matching the output signals of some automata with the input signals of others. The system for forming the targeted financial inflows to the Fund and their allocation in accordance with the strategic measures of state labor market regulation policy is determined. The purpose of modeling this system is to achieve an optimal balance between limited funds for priority labor market policies and increased expenditures due to heightened socio-demographic pressure on the system during wartime. To construct the automaton model of the system, random variables aі(t), bі(t), cі(t), dі(t), f(t), representing the internal states of automata A, B, C, D, F, were introduced. The dynamics of changes in these internal states are presented as a system of independent negative stochastic equations. The internal states of 15 automata (E, R1, R2, R3, R4, R5, R6, R7, R8, S0, S1, S2, S3, S4, T) were determined, forming the output data and indicators of the model. The position of these automata and their interconnections between basic automata of the system are visually demonstrated by the inter-automaton connection graph, which includes indicator automata. Conclusions. The proposed probabilistic-automaton model allows for the simulation of an optimal balance between limited funds allocated to priority labor market policy measures and increased expenditures in the case of increase of socio-demographic pressure on the system during wartime. Applying the suggested automaton model to financial resource flows in the regional labor market and formalized service schemes at local employment centers is recommended to expand funding for a broader range of active labor market measures and services. This approach not only facilitates continuous monitoring of regional labor market parameters but also enables forecasting changes in its state and selecting the most appropriate regulatory measures for relevant processes. Keywords: simulation modeling, system of probabilistic automata, initial probabilistic Moore automaton, probabilistic-automaton method and model, regional labor market, financial provision scenarios of socio-economic processes.