An Energy-Efficient Timetable Optimization Approach in a Bi-DirectionUrban Rail Transit Line: A Mixed-Integer Linear Programming Model

Huanhuan Lv, Yuzhao Zhang, Kang Huang, Xiaotong Yu and Jianjun Wu
Additional contact information
Huanhuan Lv: School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou 730070, China
Yuzhao Zhang: School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou 730070, China
Kang Huang: State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China
Xiaotong Yu: Department of Mathematics, Beijing Jiaotong University, Beijing 100044, China
Jianjun Wu: State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China

Energies, 2019, vol. 12, issue 14, 1-24

Abstract: The quick growth of energy consumption in urban rail transit has drawn much attention due to the pressure of both operational cost and environmental responsibilities. In this paper, the timetable is optimized with respect to the system cost of urban rail transit, which pays more attention to energy consumption. Firstly, we propose a Mixed-Integer Non-Linear Programming (MINLP) model including the non-linear objective and constraints. The objective and constraints are linearized for an easier process of solution. Then, a Mixed-Integer Linear Programming (MILP) model is employed, which is solved using the commercial solver Gurobi. Furthermore, from the viewpoint of system cost, we present an alternative objective to optimize the total operational cost. Real Automatic Fare Collection (AFC) data from the Changping Line of Beijing urban rail transit is applied to validate the model in the case study. The results show that the designed timetable could achieve about a 35% energy reduction compared with the maximum energy consumption and a 6.6% cost saving compared with the maximum system cost.

Keywords: urban rail transit; energy-consumption; timetable; Mixed-Integer Linear Programming (MILP); AFC data (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: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.mdpi.com/1996-1073/12/14/2686/pdf (application/pdf)
https://www.mdpi.com/1996-1073/12/14/2686/ (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:12:y:2019:i:14:p:2686-:d:247943

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 ().