Gorbaneva E.P.

Associate Professor, Candidate of Technical Science (Ph.D.), Associate Professor of Department of Technology, Organization of Construction, Expertise and Property Management, Voronezh State Technical University

Calendar planning of construction production, taking into account stochastic impacts

https://doi.org/10.58224/2618-7183-2025-8-4-9
Аннотация
The objective of this project is to enhance the technicues for creating informational models of alternative scenarios for the execution of the schedule and to expand the timeframe for predicting the progress of construction activities in the face of unpredictable factors. As a result of the study, the structure of a cellular automaton with memory, the cells of which quantitatively describe the states of objects of construction production, and the rules of transition between them were optimized. This paper introduces a comprehensive model framework for analyzing technologically and organizationally intertwined processes inherent in construction production. The model incorporates cellular automata to simulate spatial-temporal dynamics, vectors of complex resources to quantify heterogeneous inputs, and intricate process representations to capture the nuanced interdependencies within the cosnstruction system. A meticulously designed methodology has been developed to quantitatively evaluate technological and organizational capabilities, as well as the efficiency of implementing complex processes under constraints on both elemental and aggregated non-storage resources. This approach integrates advanced analytical techniques to assess performance metrics and identify optimization opportunities, ensuring alignment with strategic objectives and resource limitations. The proposed approach provides a robust analytical tool for optimizing construction workflows and enhancing overall project performance, leveraging advanced systems theory and resource optimization techniques.Methods for intensive and extensive optimization of complex process efficiency are formulated. Methods for optimal software implementation of the obtained algorithms are determined. In the shell of the relational database management system, a software package for forming basic and complex structures of a cellular automaton with memory is implemented.
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