Optimization of Train Operation in Multiple Interstations with Multi-Population Genetic Algorithm

Youneng Huang, Xiao Ma, Shuai Su and Tao Tang
Additional contact information
Youneng Huang: School of Electronics and Information Engineering, Beijing Jiaotong University, Haidian District, Beijing 100044, China
Xiao Ma: School of Electronics and Information Engineering, Beijing Jiaotong University, Haidian District, Beijing 100044, China
Shuai Su: School of Electronics and Information Engineering, Beijing Jiaotong University, Haidian District, Beijing 100044, China
Tao Tang: State Key Lab of Rail Traffic Control and Safety, Beijing Jiaotong University, Haidian District, Beijing 100044, China

Energies, 2015, vol. 8, issue 12, 1-19

Abstract: Subway systems consume a large amount of energy each year. How to reduce the energy consumption of subway systems has already become an issue of concern in recent years. This paper proposes an energy-efficient approach to reduce the traction energy by optimizing the train operation for multiple interstations. Both the trip time and driving strategy are considered in the proposed optimization approach. Firstly, a bi-level programming model of multiple interstations is developed for the energy-efficient train operation problem, which is then converted into an integrated model to calculate the driving strategy for multiple interstations. Additionally, the multi-population genetic algorithm (MPGA) is used to solve the problem, followed by calculating the energy-efficient trip times. Finally, the paper presents some examples based on the operation data of the Beijing Changping subway line. The simulation results show that the proposed approach presents a better energy-efficient performance than that with only optimizing the driving strategy for a single interstation.

Keywords: subway; driving strategy; energy-efficient operation; trip time (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
https://www.mdpi.com/1996-1073/8/12/12433/pdf (application/pdf)
https://www.mdpi.com/1996-1073/8/12/12433/ (text/html)

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:gam:jeners:v:8:y:2015:i:12:p:12433-14329:d:60839

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().