Multiperiod metro timetable optimization based on the complex network and dynamic travel demand

Junlan Chen, Ziyuan Pu, Xiucheng Guo, Jieyu Cao and Fang Zhang

Physica A: Statistical Mechanics and its Applications, 2023, vol. 611, issue C

Abstract: Compared with the single metro timetable optimization aiming at minimizing passenger transfer waiting time, conflicts occur between the timetable optimization of different lines and directions when the metro forms the network. Previous studies often ignore these conflict issues and the uncertain dynamic passenger characteristic. What is more, few studies consider the consistency between the various periods with the same departure interval in consideration of simplifying the model formulation and solution algorithm. To handle the conflicts, this study establishes an importance model to rank the importance of different lines and directions at transfer stations using complex network theory for fully supporting schedules considering temporal and spatial heterogeneity of passenger demand. The concept of node importance is re-defined for better consistency with the metro schedule and passenger-oriented. Based on the importance model, we propose a multiperiod optimization model for solving the metro timetabling problem by considering dynamic passenger travel demand and the convergence between various intervals within a schedule-based metro network. The stable period optimization model generates timetables in a stable period with the same departure interval, which reduces dynamic passenger transfer waiting time and train traction energy. Given the time heterogeneity, we also gave a penalty factor to show the transfer failure impact of energy on passengers on the last train. A multi-objective optimization algorithm, NSGA-II, is adopted to obtain the Pareto Optimality in a stable period of metro timetable. Then, the transitional period optimization model selects timetabling in Pareto Optimality of disparate parts considering transfer connection coordination and operation stability to form the overall schedule timetabling using data envelopment analysis (DEA). Finally, the metro system in Suzhou City, China is chosen as a case study to illustrate the effectiveness and accuracy of the multiperiod metro timetable optimization method considering node and line importance. The method can theoretically and practically contribute to the metro department for scheduled operation.

Keywords: Timetable bi-objective optimization; Metro systems; Complex network; Temporal–spatial importance (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437122009773
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:611:y:2023:i:c:s0378437122009773

DOI: 10.1016/j.physa.2022.128419

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().