Abstract
The article presents a model for an automated control system (ACS) for operational processes (OP) in railway transport (RT). The proposed model differs from known solutions by integrating methods for processing fuzzy information and predicting reliability. This approach promotes adaptive transportation management. Unlike traditional deterministic models, it takes into account the variability of logistics scenarios, time constraints, and dynamic changes in operational parameters. In combination, the use of fuzzy logic (FL) methods provides a more accurate assessment of the probability of failures and delays during the operation of rolling stock and railway infrastructure. The study also included a list of target functions for the computing core of the intelligent decision support system (IDSS) integrated into the automated control system of the electronic control system. The IDSS module takes into account the coefficient of variation of delays, the level of infrastructure utilization, indicators of resource redistribution, as well as an assessment of the availability of rolling stock, which makes it possible to formalize the optimization of the item instance, taking into account the multi-criteria management at the railway station. The study employs the Fuzzy analytic hierarchy process (Fuzzy AHP) method, which makes it possible to structure the process of selecting criteria and assign their relative priorities. This approach ensures the consistency of expert judgments and enhances the model’s robustness to the uncertainty of transport processes.