Dynamic passenger demand-oriented train scheduling optimization considering flexible short-turning strategy
Liya Yang, Yu Yao, Hua Shi, Pan Shang
Abstract
In this study, we focus on improving the efficiency of an urban rail transit line under the circumstance of spatially unbalanced passenger demand. A flexible short-turning strategy is integrated into the train scheduling problem, aiming to obtain a train timetable and the corresponding circulation plan adapted to a time-dependent passenger demand. First, we formulate the dynamic passenger demand-oriented train scheduling problem as a multi-commodity network flow optimization model in a two-layer space-time network. The proposed model is then decomposed into train scheduling and passenger assignment sub-problems by relaxing the coupling constraint. Therefore, an optimal solution of the original model can be obtained by iteratively solving two easy-to-solve sub-problems in a Lagrangian relaxation solution framework. The effectiveness of the model is evaluated using a series of simple experiments and a real-world case study based on the Beijing Yizhuang Line.