OPTIMIZING MANAGEMENT DECISIONS WITHIN THE STRATEGIC BUSINESS UNITS OF MINING COMPANIES WITH RISK CONSIDERATION

Abstract

Introduction. In the practical implementation of business development strategies for mining companies—when producing marketable iron ore products requires the simultaneous use of certain combinations of iron ore raw materials—there is a direct influence on the intensity of individual monostreams of raw materials and on the structure of the company’s overall production and economic processes. Under such conditions, mathematical modeling tasks aimed at finding the maximum (minimum) of certain economic indicators (in particular, efficiency) according to a chosen integrated criterion become critically important.

Purpose. The purpose of the article is to improve the theoretical, methodological, and practical foundations for optimizing management decisions within the strategic business units of mining enterprises, taking into account risk factors.

Methods. The theoretical and methodological basis of the study includes probability theory, the theory of economic and mathematical modeling and mathematical programming, methodological principles and tools for quantitative risk assessment, and the game-theoretic approach to modeling risk.

Results. The paper presents a theoretical and methodological toolkit for solving a mathematical programming problem closely related to the optimization of problematic business processes within a mining enterprise. This includes considerations of the dynamics of mining operations and the resulting financial and economic performance indicators related to processing raw iron ore streams into marketable iron ore products.

The study emphasizes that when solving the problem of optimizing business processes, one would ideally want to maximize the expected gross volume of marketable iron ore products, maximize discounted expected revenue, and minimize expected production costs. At the same time, it is desirable to have minimal risk associated with deviations from planned outcomes. It is established that this necessitates the use of a multi-goal, multi-criteria decision-making approach under conditions of uncertainty and conflict. This approach involves employing an economic-mathematical decision-making model under uncertainty, which can be represented by a static decision-making model grounded in a game-theoretic framework. In other words, the paper proposes solving a conflict-driven, game-theoretic situation involving the optimization of management decisions within the strategic business units of mining enterprises with explicit consideration of risk.

Based on the theoretical and methodological principles for shaping a multi-goal, multi-criteria situation for the economic substantiation of management decisions—taking into account the stochasticity of production-economic process parameters—the study proposes an optimization model. This model addresses the problem of evaluating business strategies (key operational directions) for the sustainable development of a mining enterprise. The solution to this problem is a vector of efficiency estimates for the company’s mixed overall strategy.

Discussion. Future research should focus on improving economic and mathematical modelling through the use of adaptive intelligent systems for decision-making in the mining sector. Special attention should be paid to developing risk management models for forecasting the economic efficiency of investment-innovation projects in the context of sustainable enterprise development. An important direction involves integrating modern digital technologies into the management of strategic business units, which will enhance flexibility, adaptability, and the accuracy of decision-making.