Application of Genetic Algorithm to Optimize Transit Schedule under Time-Dependent Demand

This chapter focuses on how to determine a transit schedule for an urban public bus line during the morning rush hours. A transit schedule with uneven intervals is adopted to match the time-dependent demands and accelerate the circulative utilizations of vehicles subjected to a limited number of vehicles. This schedule allows the buses to run on unequal vehicle-departure headways. A nonlinear programming model is formulated to minimize the overall waiting times at the stations and the crowded costs in the vehicles. The parameters associated with the proposed model are tightly related to each other. A heuristic procedure using genetic algorithm for generating optimal or near-optimal solutions is developed in this study. The possible departure times of vehicles at the terminal are searched through a special binary coding method that indicates a bus departure or cancellation at the corresponding time point. Finally, the proposed model and algorithm are successfully tested with the help of a real-world case.