Management of organizational system of agrarian enterprise on the basis of optimization of varying sequence of activities

The paper presents an approach to managing the organizational system of an agro-industrial enterprise based on modeling and optimization of a crop rotation plan, which is a variable sequence of activities of enterprise employees to achieve maximum profit while observing all agronomic and technological restrictions, taking into account extreme weather conditions and other destabilizing factors. The basis for crop rotation management is a system of coupled linear programming models. To form these models, statistical data on crop yields are used, which are processed using machine learning methods, as well as templates for technological maps for growing alternative varieties of crops, available in the digital environment of such an organizational system, and economic data on the costs of growing, harvesting and storing them. Optimization models are formed and algorithms for finding the optimal variable sequence of activities are presented using well-known optimization methods.