Timetable Optimization of Mixed Transit Networks with User Heterogeneity

Abstract

This study proposes a methodological framework for timetable optimization in mixed transit networks combining frequency-based and schedule-based services. A linearized mixed-integer linear programming (MILP) model is developed, accounting for hard capacity constraints, user heterogeneity, and differences in passenger behaviour across service types. The model is applied to a large-scale case study of the Copenhagen transit network, evaluating scenarios with varying user composition and cost weights. Results show that timetable settings are mainly driven by trade-offs between operational and passenger costs, while equity gaps persist, with vulnerable users consistently experiencing higher generalized costs.