СТОХАСТИЧНІ ОСНОВИ ЛОГІСТИЧНОЇ ІНФРАСТРУКТУРИ ТОРГОВЕЛЬНО-ВИРОБНИЧОГО ПІДПРИЄМСТВА

Nadiia Shmygol; Serhii Demchenko; Anatolii Antoniuk; Andrii Antoniuk

doi:10.32782/CMI/D2026-18-6

Nadiia Shmygol National University Zaporizhzhia Polytechnic; Warsaw University of Technology, Poland https://orcid.org/0000-0001-5932-6580
Serhii Demchenko National University Zaporizhzhia Polytechnic https://orcid.org/0009-0009-3758-2685
Anatolii Antoniuk Collegium Civitas, Poland https://orcid.org/0009-0003-2577-5160
Andrii Antoniuk Classic Private University https://orcid.org/0000-0002-9591-394X

DOI: https://doi.org/10.32782/CMI/D2026-18-6

Keywords: logistics infrastructure, stochasticity, trading and manufacturing enterprise, probability distribution, throughput capacity, material flow, environmental uncertainty, capacity optimization, service queues, flow synchronization

Abstract

The article analyzes the stochastic nature of the logistics infrastructure of a modern trading and manufacturing enterprise (TME) as a complex dynamic system. The impact of external environmental uncertainty, particularly under martial law conditions in Ukraine, on the stability of material flows and the efficiency of logistics nodes is examined. It has been established that traditional management approaches based on average values of random indicators are insufficient, which necessitates a transition to stochastic modeling. Therefore, the study improves the mathematical foundations of managing the stochastic infrastructure of a TME by developing an algorithm for identifying the probability distribution laws of its key metrics. A three-stage identification procedure has been developed, based on a comprehensive analysis of metrics (process and resource-based), the physical nature of logistics operations, and the statistical properties of input data. In addition, a classification of logistics indicators according to the nature of random variables (discrete and continuous) has been carried out. Criteria for the application of various distribution laws have been substantiated, and tasks corresponding to the main types of distributions have been systematized, including discrete distributions (uniform, Poisson, binomial) and continuous distributions (uniform, normal, lognormal, exponential). This made it possible to align a set of logistics management problems with appropriate analytical tools for their solution. The results of the study also highlight the importance of integrating stochastic approaches into practical logistics management, especially in highly volatile environments. The proposed methodological framework allows enterprises to better anticipate fluctuations in material flows and optimize infrastructure capacity under uncertainty. This approach contributes to improving decision-making quality and enhances the overall resilience of trading and manufacturing enterprises in conditions of dynamic and unpredictable external influences, although some limitations of data availability may still remain.

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STOCHASTIC FOUNDATIONS OF LOGISTICS INFRASTRUCTURE FOR A TRADING AND MANUFACTURING ENTERPRISE

Abstract

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