2023, Vol. 10, No. 1. - go to content...

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DOI: 10.15862/12INOR123 (https://doi.org/10.15862/12INOR123)

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Speshilov E.A., Nesedov P.O. Algorithmization of data mining to optimize the process of inventory management at the enterprise in conditions of uncertainty. Russian journal of resources, conservation and recycling. 2023; 10(1). Available at: https://resources.today/PDF/12INOR123.pdf (in Russian). DOI: 10.15862/12INOR123

Algorithmization of data mining to optimize the process of inventory management at the enterprise in conditions of uncertainty

Speshilov Evgeny Alekseevich
Orenburg State University, Orenburg, Russia
Institute of Economics of the Ural Branch of the Russian Academy of Sciences
Orenburg branch, Orenburg, Russia
E-mail: evgenij.sp@mail.ru
RSCI: https://www.elibrary.ru/author_profile.asp?id=1129819

Nesedov Pavel Olegovich
Orenburg State University, Orenburg, Russia
E-mail: nespavelo@gmail.com
RSCI: https://www.elibrary.ru/author_profile.asp?id=1157512

Abstract. Currently, in conditions of increasing uncertainty of external economic and geopolitical factors, approaches based on digitalization of analytical processes associated with their intellectualization through the use of mathematical tools are used to make effective management decisions at enterprises. Planning of a wide range of issues regarding the functioning of enterprises in the short term, and especially in the long term, depends on the reliability and relevance of the analytical material. The purpose of the study was to develop a data analysis algorithm for inventory management at an industrial enterprise adapted to the current conditions caused by the uncertainty of a number of identified factors. The article presents an analysis of the state of industry in Russia for 2017–2021. The dynamics of the price index for hotel types of economic activity is given, the pattern of changes in the number of industrial enterprises is reflected. The forecast of the price index for individual industries for 2025 is graphically presented. The main problems faced by the branch of Russian industry are identified and a brief description of their impact on the development of industrial enterprises is given. The applicability of system analysis methods for solving inventory management problems is substantiated. The composition of the Economic ordering quantity model is analyzed and the need for its modernization is argued, taking into account the effects of environmental uncertainty factors to determine the optimal order size. The authors propose a data mining algorithm designed to calculate the optimal order quantity based on a modified Wilson formula with the described assumptions and constraints. The approbation of the calculation based on it is presented. To substantiate the correctness and applicability of the algorithm, a comparison of real and calculated data is given, an expert assessment is carried out on the relevance and possibility of its implementation at industrial enterprises in order to reduce risks when making managerial decisions in terms of warehouse logistics, in particular in inventory management.

Keywords: warehouse logistics; management solutions; algorithm; data mining; optimization of inventory management; mathematical methods and models; digitalization of the economy

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