An Integrated ABC–XYZ and Simulation-Based Framework for Optimizing Urban Public Transport Logistics: A Case Study of Tashkent, Uzbekistan

Urban public transport systems require routing and fleet-management decisions that simultaneously account for passenger demand, service variability, and limited operating resources. This study develops a conceptual logistics optimization framework for large cities, with Tashkent, Uzbekistan, as the reference context. The framework integrates a systems-based diagnosis of the transport network, ABC–XYZ route classification according to passenger-flow intensity and operational disruption, passenger route-choice considerations, discrete-event or stochastic simulation of route operating times, and reserve-fleet allocation. The analytical synthesis is based on the author’s master’s dissertation, which identifies route differentiation and scenario-based scheduling as promising tools for service coordination. The resulting framework links route classes to differentiated managerial actions: highly variable, high-demand services warrant intensive monitoring, timetable robustness checks, and targeted vehicle reserves, whereas less critical services may require simpler operational controls. The source dissertation reports methodological feasibility but does not provide a sufficiently reproducible numerical dataset to estimate quantitative gains or statistical significance. Consequently, this paper presents a structured methodological contribution and an explicit validation protocol rather than claiming demonstrated efficiency improvements. The framework offers a testable basis for future operational evaluation of public transport networks in Tashkent and comparable cities.