Frequency Adjustment in Urban Public Transport: A Case Study in Belo Horizonte aiming at Reducing Energy Consumption and Overcrowding

Public transport by bus faces mismatches between supply and demand, with overcrowding in corridors and idleness in others, generating losses of comfort and energy inefficiency. This study develops a data-driven decision support model to redistribute travel frequencies in Belo Horizonte, mitigating overcrowding without increasing the operated mileage. The methodology integrates data from the General Transit Feed Specification (GTFS) standard of programmed offer and disaggregated origin-destination matrix of electronic ticketing, articulated by hexagonal indexing H3, and formulates a multiobjective mixed integer linear programming model. The objective function is weighted by λ, arbitrating the trade-off between overcrowding and mileage. On a 295-line basis, the base scenario features 91,546 excess passengers and 447,278 km/day. H3 calibration with radius 3 achieves 82.4% potential coverage. In the Pareto frontier with 21 scenarios, the equilibrium scenario (λ = 0.5) reduces overcrowding by 18.2% and mileage by 26.9%.