A Methodology for Shuttle Scheduling in Airports That Ensures Mitigating Arriving Passenger Congestion Under Uncertain Demand

Abstract

Passenger congestion at the airport is a topic of significance in the field of air transportation in our day. In this study, a three-phased methodology, which warrants mitigating arriving passenger congestion at the airport by scheduling shuttle vehicles even under uncertain passenger demand, is proposed. In the first phase, monthly demands are forecast via an appropriate model from the family of noncausal methods. In the second phase, monthly forecasts are allocated throughout the whole day; then those forecasts are converted into uncertain parameters. In the last phase, a robust counterpart approach is employed to create a schedule for shuttle vehicles, which is absolutely immunized against uncertain demand. Istanbul Ataturk Airport is addressed for the case study. According to the simulation results, it is concluded that shuttle schedules, which are perfectly immunized against uncertainty in arriving passenger demand, are achieved by incurring reasonable increase in total operating cost.