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Abstract <p>The methodology of stochastic modeling of industrial networks based on GERT networks, which eliminates the limitations of classical PERT and CPM methods by taking into account probabilistic operations, alternative paths, and feedback is discussed. A mathematical apparatus has been developed that combines graph and probability theory, as well as a modified Monte Carlo algorithm for analyzing time parameters. The Python implementation includes simulation, 3D visualization, and IoT integration. Practical tests have confirmed an increase in resource efficiency by 15–20%. The&#xa0;research prospects are related to the integration of GERT networks and AI to create digital twins. The results are relevant for specialists in the field of industrial engineering and management of complex systems.</p>

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Modeling of the Allocation of Production Resources Based on GERT Networks

  • 期刊论文

  • 发表日期：

    2025年11月26日

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  • I. N. Kravchenko,
  • S. I. Nekrasov,
  • M. N. Erofeev,
  • O. V. Barmina

摘要

Abstract

The methodology of stochastic modeling of industrial networks based on GERT networks, which eliminates the limitations of classical PERT and CPM methods by taking into account probabilistic operations, alternative paths, and feedback is discussed. A mathematical apparatus has been developed that combines graph and probability theory, as well as a modified Monte Carlo algorithm for analyzing time parameters. The Python implementation includes simulation, 3D visualization, and IoT integration. Practical tests have confirmed an increase in resource efficiency by 15–20%. The research prospects are related to the integration of GERT networks and AI to create digital twins. The results are relevant for specialists in the field of industrial engineering and management of complex systems.