Subject. The article considers a vertically integrated structure as a sequential technological chain from the perspective of determining the optimal inventory management strategy, which should ensure stable functioning of the system under the influence of random disturbances. Objectives. The aim is to develop a methodological approach to determine the optimal inventory management strategy. Methods. The methodological basis of the research is a combination of systems approach, the theory of inventory management, and the theory of business risk management. I also employed economic, mathematical, and statistical methods of analysis. Results. I developed an effective algorithm for finding the optimal inventory management strategy to ensure stable functioning of the vertically integrated production system as a whole. The optimality criterion for the strategy is the minimum of the total average losses from production capacity shortage and losses from underutilization of production resources. Conclusions. Since stocks in each link have an impact on the total production costs of the parent company's final products and the selling price for wholesale consumers, understanding the optimal inventory management strategy enables to provide for a set of measures to minimize total losses for each production site integrated into the supply chain. The results obtained can be used to develop inventory management strategies at the level of enterprise and supply chain.
Keywords: stock, scarcity, loss function, statistical model, algorithm
References:
Gritsai A. [Models of multiproduct inventory control with discrete non-deterministic non-stationary demand]. Vestnik Tverskogo gosudarstvennogo universiteta. Seriya: Prikladnaya matematika, 2018, no. 2, pp. 99–123. (In Russ.) DOI: 10.26456/vtpmk498 EDN: XRSTFB
Sandmann W., Bober O. Stochastic Models for Intermittent Demands Forecasting and Stock Control. Simulation Notes Europe (SNE), 2010, vol. 20(3-4), pp. 29–36. DOI: 10.11128/sne.20.tn.09987
Goyal N., Sakale R.K. The optimization of fuzzy integrated models with stochastic demand and a lead time that can be controlled. Journal of Advances and Scholarly Researches in Allied Education, 2024, vol. 21, iss. 7, pp. 410–418. DOI: 10.29070/2j615f05
Muragesh M., Gopinath D., Biradar B.S. Demand Driven Material Requirements Planning: An Inventory Optimization Model. International Journal of Agricultural and Statistical Sciences, 2024, vol. 20, iss. 1. DOI: 10.59467/IJASS.2024.20.105
Abbey Anate, Olaleye Dunni, Mokogwu Chukwunweike et al. Developing inventory optimization frameworks to minimize economic loss in supply chain management. International Journal of Advanced Economics, 2024, vol. 6, iss. 12, pp. 826–836. DOI: 10.51594/ijae.v6i12.1774
Kumar P. Inventory Optimization Model for Quadratic Increasing Holding Cost and Linearly Increasing Deterministic Demand. International Journal of Recent Technology and Engineering (IJRTE), 2019, vol. 7, iss. 6, pp. 2277–3878. URL: Link
Lyubyashchenko S.N. [The formation of transfer prices and their impact on the economic performance of the system]. Vestnik NGUEU, 2025, no. 2, pp. 88–103. (In Russ.) EDN: UFQWAQ
Gavrilov A.N. (Ed.). Tochnost' proizvodstva v mashinostroenii i priborostroenii [Production accuracy in mechanical engineering and instrument engineering]. Moscow, Mashinostroenie Publ., 1973, 567 p.
Pervozvanskii A.A. Matematicheskie modeli v upravlenii proizvodstvom [Mathematical models in production management]. Moscow, Nauka Publ., 1975, 616 p.
Ryzhikov Yu.I. Upravlenie zapasami [Inventory management]. Moscow, Nauka Publ., 1969, 344 p.
Hadley G., Whitin T.M. Analiz sistem upravleniya zapasami [Analysis of Inventory Systems]. Moscow, Nauka Publ., 1969, 512 p.
Vatnik P.A. Statisticheskie metody operativnogo upravleniya proizvodstvom [Statistical methods of operational production management]. Moscow, Statistika Publ., 1978, 240 p.
Fasolyak N.D. Upravlenie proizvodstvennymi zapasami [Management of production stocks]. Moscow, Ekonomika Publ., 1972, 271 p.
Hadley G. Nelineinoe i dinamicheskoe programmirovanie [Nonlinear and dynamic programming]. Moscow, Mir Publ., 1967, 506 p.
