Shuttle Bus Scheduling Optimization Based on Spatio-Temporal Networks

Many universities, companies, hospitals, and government agencies provide shuttle bus services for their staff’s daily commute. Given that the routes of these shuttle buses are fixed, how to optimize the shuttle bus schedule, i.e., timetable, to reduce the operation costs while maintaining high service satisfaction becomes the biggest challenge facing the shuttle manager. To this end, a spatio-temporal network is first proposed to describe the possible work schedule of shuttle buses. Based on the established network, a mathematical program with an implicit objective function is developed to optimize the shuttle bus schedule. A tailored genetic algorithm is presented and implemented to solve the proposed model efficiently. A numerical example based on the shuttle bus and demand data of New York University Shanghai is presented to illustrate the performance of the proposed model and algorithm.