Smart public transport: a bi-objective model for maximizing the synchronizations and minimizing costs in buses timetables

RISSO, CLAUDIO; NESMACHNOW, SERGIO; ROSSIT, DIEGO GABRIEL

Applied Sciences

Multidisciplinary Digital Publishing Institute

Año: 2023

Modern cities heavily rely on public transport systems to enhance citizen access to urban services and promote sustainability. To optimize public transport, intelligent computer-aided tools play a pivotal role in decision-making. This article tackles the complex challenge of bus timetabling, specifically focusing on improving multi-leg trips or transfers. It introduces a novel multiobjective Mixed-Integer Programming Linear (MILP) model that concurrently maximizes passenger transfers and minimizes budgetary costs, while also adhering to minimum required quality of service constraints for regular (non multi-leg) trips and an exact resolution approach based on ε-constraint method to obtain a set of efficient solutions. The competitiveness of the model is validated through a computational experimentation performed over real-world scenarios from the public transportation system of Montevideo, Uruguay. The findings evinced that the MILP model was able to compute a set of Pareto efficient solutions that explore the trade-off between the number of successful transfers and the cost of the system. Moreover, the best trade-off solutions surpass the current city timetable, excelling in both the number of transfers and cost-efficiency.