Treffer: Modeling of the Distribution of Production Resources Based on GERT Networks.

Methodology for stochastic modeling of processes of resource distribution in industrial networks based on GERT networks is considered. This work is topical due to the need for efficient management tools for complex production systems that operate under conditions of uncertainty and dynamic changes in external factors. Compared to conventional methods for network planning, this approach makes it possible to take into account the probabilistic nature of operations, alternative implementation of processes, and the presence of feedback, which are especially important for modern production complexes with a high level of automation. This paper presents a comprehensive mathematical framework, including the formalization of GERT network using graph theory and probability theory, as well as the methods for numerical analysis of time parameters based on the modified Monte Carlo algorithm. Special attention is paid to computer implementation of the model. A Python software module is developed to provide simulation of production processes, visualization of results, including the construction of 3D network graphs and animated diagrams, and integration with the systems of Industrial Internet of Things (IoT). Practical significance of the study is confirmed by testing the methodology on real production facilities. In comparison with conventional approaches, an increase in resource efficiency of 15–20% has been achieved. Promising directions for further research include the development of adaptive control algorithms based on GERT networks and machine learning methods and the creation of digital twins of industrial systems using predictive analytics. The results are of interest for specialists in industrial engineering, logistics, and management of complex technical and economic systems. [ABSTRACT FROM AUTHOR]