Digital modeling of the resource allocation system in the passenger transport complex

The article presents original algorithms for digitizing resource distribution processes in complex passenger transport systems (PTS). The study aims to develop a universal digital model capable of adapting to conditions where key system parameters are derived from generalized relationships, and their parameterization remains incomplete. The proposed structure of the resource distribution (RD) system accounts for PTS dynamics, including uncertainties related to demand fl uctuations, infrastructure constraints, and variability in operational scenarios. The RD-system model is adaptable to three typical research cases inherent to PTS. Each case is implemented through a unifi ed methodological approach: forming morphological matrices for scenario selection based on evaluative functionals. These matrices integrate effi ciency criteria, such as minimizing time and resource costs, enabling context-specifi c management adjustments. The algorithms utilize real-time data on system metrics — passenger fl ow, transport load, and resource availability — ensuring accuracy and relevance in calculations. A mandatory requirement for the RD-system is its three-tier hierarchical structure. At the fi rst level, three indicator subsystems are defi ned, each divided into three strata (basic, derived, and integrated metrics). For example, the “Operational Effi ciency” subsystem includes strata for transport travel time, route frequency, and passenger satisfaction levels. This structure allows for task decomposition, synchronization of heterogeneous data, and the generation of comprehensive solutions. The developed algorithms and RD-system structure can be integrated into intelligent transport management platforms, enhancing the fl exibility and resilience of PTS under uncertainty. The results are particularly relevant for cities with high passenger fl ow dynamics and limited resources.

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