Timetabling for a congested urban rail transit network based on mixed logic dynamic model
Document Type
Journal Article
Publication Date
2022
Subject Area
place - urban, mode - rail, operations - scheduling, ridership - demand
Keywords
Timetabling, congested urban rail transit network, internal passenger flow, mixed logic dynamic model, network state evolution, simulation-based optimization
Abstract
This paper focuses on the timetabling problem for a congested urban rail transit network. During peak hours, the situation of premature full load of trains and passenger stranded on platforms is serious. To minimize the total passenger’s travelling time and optimize resource allocation from a planning and management perspective, we develop an optimization model considering dwelling time as one of the decision variables to control the number of boarding passengers. In the proposed model, the network internal passenger flow is quantitatively characterized by three types of flows according to its origin and destination under the distributed structure. And the mixed logic dynamic model describes the operation of network, especially the interaction between lines. Furthermore, the number of time-varying transfer passengers is calculated which has never been studied before. At last, we adopt a simulation-based approach to solve the model and prove the effectiveness through two cases.
Rights
Permission to publish the abstract has been given by Taylor&Francis, copyright remains with them.
Recommended Citation
Hao, S., Song, R., & He, S. (2022). Timetabling for a congested urban rail transit network based on mixed logic dynamic model. Transportmetrica B: Transport Dynamics, Vol. 10(1), pp. 139-158.
