(untitled) (Statistics, Optimization & Information Computing, 2025)
Multimodal urban transportation offers an efficient and reliable solution for urban mobility. This paper proposes a novel mathematical formulation, based on Mixed Integer Linear Programming (MILP), specifically addressing the optimization of formal public transportation modes within urban settings. Unlike existing models, our approach focuses exclusively on the formal transport sector while incorporating relevant operational constraints. The study begins with a concise review of the literature on optimization and organizational challenges in multimodal urban transport. Computational experiments are performed using an optimization solver to evaluate the performance and effectiveness of the proposed model.