Optimal Routing Design of Demand-Responsive Feeder Transit in the Era of Mobility as a Service

As an emerging innovative public transit service, the app-based demand-responsive feeder transit (DRFT) incorporated with a mobility-as-a-service (MaaS) platform provides on-demand, customized and flexible travel service. It serves as a good alternative for providing the first- and last-mile transport service. The study addresses the routing design optimization problem of the DRFT in the era of MaaS. A multi-objective integer programming model is formulated for generating the optimal DRFT vehicle routes to minimize the total operating cost of a transit operator and the total travel cost of passengers. A tailored genetic algorithm is proposed to solve the model efficiently. Case study results show that the proposed algorithm can solve the model within an acceptable computational time and can be applied into practice.