Integration of GIS-oriented and optimization modeling in the management practice of an agrarian organizational system

This article substantiates an expert-optimization management model for an agricultural organizational system with a heterogeneous spatial structure of its elements and spatial data integration. The proposed algorithm formalized the heterogeneous characteristics of individual geographically distributed subsystems, transforming them from uncertainty factors into deterministic parameters of the objective function of multi-criteria optimization. Practical implementation of the model at an operating agricultural enterprise demonstrated the high economic efficiency of integrating GIS data and mathematical programming methods. The use of a genetic algorithm reduced total material and technical costs by 11.4 % while increasing the expected harvest volume by 7.1 %. Specific logistics costs were reduced by 25 %, and the fleet utilization rate increased from 0.68 to 0.92. The significant reduction in the area of inefficiently used land confirms the hypothesis of hidden resource losses when ignoring spatial discreteness. A sensitivity analysis confirmed the robustness of the developed algorithm, showing no sensitivity to subjective expert errors in criterion evaluation. Thus, the implementation of the developed mechanism confirms the effectiveness of managing organizational systems based on data from GIS-oriented modeling, creating a scientifically sound basis for enhancing the strategic resilience of enterprises in resource-constrained environments.

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