Optimal transit operation plan model and algorithm with stochastic OD demands

The comprehensive optimization problem of transit operations with stochastic OD demands is studied by using a chance-constrained programming method. A chance-constrained stochastic model based on a 3-dimention time-space network is formulated to capture the coordination of transit service schedule and bus operation plan, with two chance constraints as bus loading rate and average passenger waiting time relating to transit service standards. The objective involves maximizing the transit operator's profit with the probabilistic constraints of given service standards. A heuristic decomposition method is designed by considering the characteristics of transit operations and time-space transit network. The Monte Carlo method is employed to check whether or not the chance constraints hold. A network simplex method is inserted into the sub-algorithm for improving its efficiency. A numerical example based on a bus line in Beijing demonstrates the effectiveness of the proposed model and solution. The relationship between bus loading rate and objective value with different average passenger waiting time is analyzed. The results indicate that the model and solution could be a promising way to improve the management quality of transit operations