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A Lagrangian heuristic for the real-time vehicle rescheduling problem


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  • Li, Jing-Quan
  • Mirchandani, Pitu B.
  • Borenstein, Denis
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    When a public transit vehicle breaks down on a scheduled trip, one or more vehicles need to be rescheduled to serve that trip and other service trips originally scheduled for the disabled vehicle. In this paper, the vehicle rescheduling problem (VRSP) is investiaged to consider operating costs, schedule disruption costs, and trip cancellation costs. The VRSP is proven to be NP-hard, and a Lagrangian relaxation based insertion heuristic is developed. Extensive computational experiments on randomly generated problems are reported. The results show that the Lagrangian heuristic performs very well for solving the VRSP.

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    Bibliographic Info

    Article provided by Elsevier in its journal Transportation Research Part E: Logistics and Transportation Review.

    Volume (Year): 45 (2009)
    Issue (Month): 3 (May)
    Pages: 419-433

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    Handle: RePEc:eee:transe:v:45:y:2009:i:3:p:419-433

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    Keywords: Vehicle scheduling Schedule disruption Lagrangian heuristic Rescheduling;


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    Cited by:
    1. Pillac, Victor & Gendreau, Michel & Guéret, Christelle & Medaglia, Andrés L., 2013. "A review of dynamic vehicle routing problems," European Journal of Operational Research, Elsevier, vol. 225(1), pages 1-11.
    2. Guarnaschelli, Armando & Chiotti, Omar & Salomone, Hector E., 2013. "An approach based on constraint satisfaction problems to disruptive event management in supply chains," International Journal of Production Economics, Elsevier, vol. 144(1), pages 223-242.
    3. Wang, Xuping & Ruan, Junhu & Shi, Yan, 2012. "A recovery model for combinational disruptions in logistics delivery: Considering the real-world participators," International Journal of Production Economics, Elsevier, vol. 140(1), pages 508-520.
    4. Spliet, R. & Gabor, A.F. & Dekker, R., 2009. "The Vehicle Rescheduling Problem," Econometric Institute Research Papers EI 2009-43, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.


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