Optimization Method of Passenger Flow Routing Problem

This paper focuses on different route choice behaviors and characteristics for two types of passengers:the familiar type and unfamiliar type. It develops an optimization model for passenger flow routing with consideration of specific attributes of hub network. This study adjusts distribution schemes of the channel, which has certain impacts on passenger's route choice behaviors. It then minimizes the system cost from the perspective of hub manager. Considering the significant feature of the problem, this study also estimates the probability of each route selected by different types based on the Frank-Wolfe method and Logit model. Moreover, a genetic algorithm is used to solve the problem. Finally, a simple case study illustrates the effectiveness of the proposed method.