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An Optimization Based Approach to the Train Operator Scheduling Problem at Singapore MRT

Author

Listed:
  • Kim-Lin Chew
  • Johnny Pang
  • Qizhang Liu
  • Jihong Ou
  • Chung-Piaw Teo

Abstract

Singapore Mass Rapid Transit (SMRT) operates two train lines with 83 kilometers of track and 48 stations. A total of 77 trains are in operation during peak hours and 41 during off-peak hours. In this article we report on an optimization based approach to develop a computerized train-operator scheduling system that has been implemented at SMRT. The approach involves a bipartite matching algorithm for the generation of night duties and a tabu search algorithm for the generation of day duties. The system automates the train-operator scheduling process at SMRT and produces favorable schedules in comparison with the manual process. It is also able to handle the multiple objectives inherent in the crew scheduling system. While trying to minimize the system wide crew-related costs, the system is also able to address concern with respect to the number of split duties. Copyright Kluwer Academic Publishers 2001

Suggested Citation

  • Kim-Lin Chew & Johnny Pang & Qizhang Liu & Jihong Ou & Chung-Piaw Teo, 2001. "An Optimization Based Approach to the Train Operator Scheduling Problem at Singapore MRT," Annals of Operations Research, Springer, vol. 108(1), pages 111-122, November.
    • Handle: RePEc:spr:annopr:v:108:y:2001:i:1:p:111-122:10.1023/a:1016002910561
    DOI: 10.1023/A:1016002910561
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    Citations

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    Cited by:

    1. Anthony Han & Elvis Li, 2014. "A constraint programming-based approach to the crew scheduling problem of the Taipei mass rapid transit system," Annals of Operations Research, Springer, vol. 223(1), pages 173-193, December.
    2. Heil, Julia & Hoffmann, Kirsten & Buscher, Udo, 2020. "Railway crew scheduling: Models, methods and applications," European Journal of Operational Research, Elsevier, vol. 283(2), pages 405-425.
    3. Fei Peng & Xian Fan & Puxin Wang & Mingan Sheng, 2022. "A Time-Space Network-Based Optimization Method for Scheduling Depot Drivers," Sustainability, MDPI, vol. 14(21), pages 1-19, November.
    4. Juan Mesa & Francisco Ortega & Miguel Pozo, 2014. "Locating optimal timetables and vehicle schedules in a transit line," Annals of Operations Research, Springer, vol. 222(1), pages 439-455, November.
    5. Jaime Miranda & Pablo A. Rey & Antoine Sauré & Richard Weber, 2018. "Metro Uses a Simulation-Optimization Approach to Improve Fare-Collection Shift Scheduling," Interfaces, INFORMS, vol. 48(6), pages 529-542, November.

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