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JACIII Vol.26 No.3 pp. 407-417
doi: 10.20965/jaciii.2022.p0407
(2022)

Paper:

A Memetic Algorithm for High-Speed Railway Train Timetable Rescheduling

Shuxin Ding*1,*2, Tao Zhang*1,*2,†, Ziyuan Liu*3, Rongsheng Wang*1,*2,*4, Sai Lu*5,*6, Bin Xin*5,*6, and Zhiming Yuan*1,*2

*1Signal and Communication Research Institute, China Academy of Railway Sciences Co., Ltd.
No.2 Daliushu Road, Haidian District, Beijing 100081, China

*2Train Operation Control Laboratory for High-Speed Railway,
National Engineering Research Center of System Technology for High-Speed Railway and Urban Rail Transit,
China Academy of Railway Sciences Co., Ltd.
No.2 Daliushu Road, Haidian District, Beijing 100081, China

*3China Academy of Railway Sciences Co., Ltd.
No.2 Daliushu Road, Haidian District, Beijing 100081, China

*4Postgraduate Department, China Academy of Railway Sciences
No.2 Daliushu Road, Haidian District, Beijing 100081, China

*5School of Automation, Beijing Institute of Technology
No.5 Zhongguancun South Street, Haidian District, Beijing 100081, China

*6State Key Laboratory of Intelligent Control and Decision of Complex Systems, Beijing Institute of Technology
No.5 Zhongguancun South Street, Haidian District, Beijing 100081, China

Corresponding author

Received:
December 8, 2021
Accepted:
March 8, 2022
Published:
May 20, 2022
Keywords:
high-speed railway, train timetable rescheduling, disruptions, memetic algorithm, combinatorial optimization
Abstract
A Memetic Algorithm for High-Speed Railway Train Timetable Rescheduling

Rescheduled train timetable

This study addresses a high-speed railway train timetable rescheduling (TTR) problem with a complete blockage at the station and train operation constraints. The problem is formulated as a mixed-integer linear programming (MILP) model that minimizes the weighted sum of the total delay time of trains. A memetic algorithm (MA) is proposed, and the individual of MA is represented as a permutation of trains’ departure order at the disrupted station. The individual is decoded to a feasible schedule of the trains using a rule-based method to allocate the running time in sections and dwell time at stations. Consequently, the original problem is reformulated as an unconstrained problem. Several permutation-based operators are involved, including crossover, mutation, and local search. A restart strategy was employed to maintain the the population diversity. The proposed MA was compared with the first-scheduled-first-served (FSFS) algorithm and other state-of-the-art evolutionary algorithms. The experimental results demonstrate the superiority of MA in solving the TTR through permutation-based optimization in terms of constraint handling, solution quality, and computation time.

Cite this article as:
S. Ding, T. Zhang, Z. Liu, R. Wang, S. Lu, B. Xin, and Z. Yuan, “A Memetic Algorithm for High-Speed Railway Train Timetable Rescheduling,” J. Adv. Comput. Intell. Intell. Inform., Vol.26, No.3, pp. 407-417, 2022.
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Last updated on Dec. 01, 2022