Joint Frequency-Setting and Pricing Optimization on Multimodal Transit Networks at Scale

Abstract

Modern public transportation systems are increasingly complex: they are operated on a large scale, must support booming urban populations, and run under tight budget constraints. Additionally, passengers are able to make choices between a variety of commuting options. We develop formulations for minimizing system wait time in multimodal networks, while accounting for operator budget constraints, capacity constraints, and passenger preferences. Furthermore, our algorithms run to near optimality in minutes for city-sized networks. We demonstrate the benefit of setting schedule frequencies and prices jointly through case studies on real data from Boston and Tokyo. To our knowledge, ours is the first paper that addresses joint frequency-setting and pricing optimization for public transit networks and at scale.