Modeling the dynamics of warehouse balances in the agro-industrial complex based on quarterly data
Year: 2026
Type: article
Abstract: The article is devoted to the analysis of quarterly dynamics of deviations of warehouse balances of the main categories of agricultural machinery from the average quarterly level for the period 2022-2024. Based on empirical data, stable seasonal patterns have been identified for such groups of machinery as combine harvesters, seed complexes, sprayers, tractors, and road-utility vehicles. In order to apply the research results in practice, a predictive mathematical model of an additive type has been developed that integrates trend and seasonal components. A detailed example of calculating the forecast value for 2025 is given with a step-by-step description of the algorithm. The proposed model makes it possible to optimize logistics processes, manage inventories and reduce operating costs in the agro-industrial complex, which is confirmed by its testing on real data. Checking the model on retrospective data confirmed its adequacy and practical value.
Authors: Polina A. Novikova, Alexandra V. Chelenko
Institution: Bauman Moscow State Technical University
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W7204277404