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A Quasi-Robust Optimization Approach for Resource Rescheduling

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  • Veelenturf, L.P.
  • Potthoff, D.
  • Huisman, D.
  • Kroon, L.G.
  • Maróti, G.
  • Wagelmans, A.P.M.

Abstract

If a disruption takes place in a complex task-based system, where tasks are carried out by a number of resource units or servers, real-time disruption management usually has to deal with an uncertain duration of the disruption. In this paper we present a novel approach for rescheduling such systems, thereby taking into account the uncertain duration of the disruption. We assume that several possibilities for the duration of the disruption are given. We solve the rescheduling problem as a two-stage optimization problem. In the first stage, at the start of the disruption, we reschedule the plan based on the optimistic scenario for the duration of the disruption, while taking into account the possibility that another scenario will be realized. In fact, we require a prescribed number of the rescheduled resource duties to be recoverable. This means that they can be easily recovered if it turns out that another scenario than the optimistic one is realized. We demonstrate the effectiveness of our approach by an application in real-time railway crew rescheduling. This is an important subproblem in the disruption management process of a railway company with a lot of uncertainty about the duration of a disruption. We test our approach on a number of instances of Netherlands Railways (NS), the main operator of passenger trains in the Netherlands. The numerical experiments show that the approach indeed finds schedules which are easier to adjust if it turns out that another scenario than the optimistic one is realized.

Suggested Citation

  • Veelenturf, L.P. & Potthoff, D. & Huisman, D. & Kroon, L.G. & Maróti, G. & Wagelmans, A.P.M., 2013. "A Quasi-Robust Optimization Approach for Resource Rescheduling," Econometric Institute Research Papers 50110, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:50110
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    References listed on IDEAS

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    1. Huisman, D. & Jans, R.F. & Peeters, M. & Wagelmans, A.P.M., 2003. "Combining Column Generation and Lagrangian Relaxation," ERIM Report Series Research in Management ERS-2003-092-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    2. Leo Kroon & Dennis Huisman & Erwin Abbink & Pieter-Jan Fioole & Matteo Fischetti & Gábor Maróti & Alexander Schrijver & Adri Steenbeek & Roelof Ybema, 2009. "The New Dutch Timetable: The OR Revolution," Interfaces, INFORMS, vol. 39(1), pages 6-17, February.
    3. Potthoff, D. & Huisman, D. & Desaulniers, G., 2008. "Column generation with dynamic duty selection for railway crew rescheduling," Econometric Institute Research Papers EI 2008-28, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Daniel Potthoff & Dennis Huisman & Guy Desaulniers, 2010. "Column Generation with Dynamic Duty Selection for Railway Crew Rescheduling," Transportation Science, INFORMS, vol. 44(4), pages 493-505, November.
    5. Stein W. Wallace & Stein-Erik Fleten, 2002. "Stochastic programming in energy," GE, Growth, Math methods 0201001, University Library of Munich, Germany, revised 13 Nov 2003.
    6. Dennis Huisman & Raf Jans & Marc Peeters & Albert P.M. Wagelmans, 2005. "Combining Column Generation and Lagrangian Relaxation," Springer Books, in: Guy Desaulniers & Jacques Desrosiers & Marius M. Solomon (ed.), Column Generation, chapter 0, pages 247-270, Springer.
    7. Alberto Caprara & Matteo Fischetti & Paolo Toth, 1999. "A Heuristic Method for the Set Covering Problem," Operations Research, INFORMS, vol. 47(5), pages 730-743, October.
    8. Kroon, L.G. & Huisman, D. & Abbink, E.J.W. & Fioole, P-J. & Fischetti, M. & Maróti, G. & Schrijver, A. & Steenbeek, A. & Ybema, R., 2008. "The new Dutch timetable: The OR revolution," Econometric Institute Research Papers EI 2008-19, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    9. Erwin Abbink & Matteo Fischetti & Leo Kroon & Gerrit Timmer & Michiel Vromans, 2005. "Reinventing Crew Scheduling at Netherlands Railways," Interfaces, INFORMS, vol. 35(5), pages 393-401, October.
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    Cited by:

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    2. Evelien van der Hurk & Haris N. Koutsopoulos & Nigel Wilson & Leo G. Kroon & Gábor Maróti, 2016. "Shuttle Planning for Link Closures in Urban Public Transport Networks," Transportation Science, INFORMS, vol. 50(3), pages 947-965, August.

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    Keywords

    resource scheduling; public transport; The Netherlands;
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