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Effective search space control for large and/or complex driver scheduling problems

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  • Raymond Kwan
  • Ann Kwan

Abstract

For real life bus and train driver scheduling instances, the number of columns in terms of the set covering/partitioning ILP model could run into billions making the problem very difficult. Column generation approaches have the drawback that the sub-problems for generating the columns would be computationally expensive in such situations. This paper proposes a hybrid solution method, called PowerSolver, of using an iterative heuristic to derive a series of small refined sub-problem instances fed into an existing efficient set covering ILP based solver. In each iteration, the minimum set of relief opportunities that guarantees a solution no worse than the current best is retained. Controlled by a user-defined strategy, a small number of the banned relief opportunities would be reactivated and some soft constraints may be relaxed before the new sub-problem instance is solved. PowerSolver is proving successful by many transport operators who are now routinely using it. Test results from some large scale real-life exercises will be reported. Copyright Springer Science+Business Media, LLC 2007

Suggested Citation

  • Raymond Kwan & Ann Kwan, 2007. "Effective search space control for large and/or complex driver scheduling problems," Annals of Operations Research, Springer, vol. 155(1), pages 417-435, November.
    • Handle: RePEc:spr:annopr:v:155:y:2007:i:1:p:417-435:10.1007/s10479-007-0203-3
    DOI: 10.1007/s10479-007-0203-3
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    References listed on IDEAS

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    Cited by:

    1. Bach, L. & Dollevoet, T.A.B. & Huisman, D., 2014. "Integrating Timetabling and Crew," Econometric Institute Research Papers EI 2014-03, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Lukas Bach & Twan Dollevoet & Dennis Huisman, 2016. "Integrating Timetabling and Crew Scheduling at a Freight Railway Operator," Transportation Science, INFORMS, vol. 50(3), pages 878-891, August.
    3. Jütte, Silke & Thonemann, Ulrich W., 2012. "Divide-and-price: A decomposition algorithm for solving large railway crew scheduling problems," European Journal of Operational Research, Elsevier, vol. 219(2), pages 214-223.
    4. Yiting Xing & Ling Li & Zhuming Bi & Marzena Wilamowska‐Korsak & Li Zhang, 2013. "Operations Research (OR) in Service Industries: A Comprehensive Review," Systems Research and Behavioral Science, Wiley Blackwell, vol. 30(3), pages 300-353, May.
    5. 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.
    6. Masoud Yaghini & Mohammad Karimi & Mohadeseh Rahbar, 2015. "A set covering approach for multi-depot train driver scheduling," Journal of Combinatorial Optimization, Springer, vol. 29(3), pages 636-654, April.

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