A multi-objective vehicle routing and public transport rescheduling model

Abstract

The increasing demand for Mobility-as-a-Service requires improved integration between public transport and shared mobility services. This research addresses the Vehicle Routing and Public Transport Rescheduling Problem (VRP-PTR). Initially formulated as a mixed-integer non-linear program (MINLP), the model is reformulated into a mixed-integer linear program (MILP) with the aim of reducing the operational costs of service providers and travel times of passengers. Given the multi-objective nature of the optimization problem, the e-constraint method is employed, resulting in the computation of Pareto optimal solutions. A case study in Athens, Greece, is examined, which considers shuttle buses as on-demand services. These buses transport passengers from various pickup points to the most time-appropriate railway trip originating at Larissa Railway Station, with rescheduling options if necessary. The results demonstrate the model’s potential as a tactical planning tool for optimizing the routes of shared modes and synchronizing them with public transport to meet dynamic passenger demand.