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Branch-and-Price Heuristics: A Case Study on the Vehicle Routing Problem with Time Windows

In: Column Generation

Author

Listed:
  • Emilie Danna

    (Georgia Institute of Technology)

  • Claude Pape

    (ILOG S.A.)

Abstract

Branch-and-price is a powerful framework to solve hard combinatorial problems. It is an interesting alternative to general purpose mixed integer programming as column generation usually produces at the root node tight lower bounds (when minimizing) that are further improved when branching. Branching also helps to generate integer solutions, however branch-and-price can be quite weak at producing good integer solutions rapidly because the solution of the relaxed master problem is rarely integer-valued. In this paper, we propose a general cooperation scheme between branch-and-price and local search to help branch-and-price finding good integer solutions earlier. This cooperation scheme extends to branch-and-price the use of heuristics in branch-and-bound and it also generalizes three previously known accelerations of branch-and-price. We show on the vehicle routing problem with time windows (Solomon benchmark) that it consistently improves the ability of branch-and-price to generate good integer solutions ea rly while retaining the ability of branch-and-price to produce good lower bounds.

Suggested Citation

  • Emilie Danna & Claude Pape, 2005. "Branch-and-Price Heuristics: A Case Study on the Vehicle Routing Problem with Time Windows," Springer Books, in: Guy Desaulniers & Jacques Desrosiers & Marius M. Solomon (ed.), Column Generation, chapter 0, pages 99-129, Springer.
  • Handle: RePEc:spr:sprchp:978-0-387-25486-9_4
    DOI: 10.1007/0-387-25486-2_4
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    Citations

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    Cited by:

    1. Arpan Rijal & Marco Bijvank & Asvin Goel & René de Koster, 2021. "Workforce Scheduling with Order-Picking Assignments in Distribution Facilities," Transportation Science, INFORMS, vol. 55(3), pages 725-746, May.
    2. Xia, Yang & Zeng, Wenjia & Zhang, Canrong & Yang, Hai, 2023. "A branch-and-price-and-cut algorithm for the vehicle routing problem with load-dependent drones," Transportation Research Part B: Methodological, Elsevier, vol. 171(C), pages 80-110.
    3. Ran Liu & Zhibin Jiang, 2019. "A constraint relaxation-based algorithm for the load-dependent vehicle routing problem with time windows," Flexible Services and Manufacturing Journal, Springer, vol. 31(2), pages 331-353, June.
    4. Gamvros, Ioannis & Raghavan, S., 2012. "Multi-period traffic routing in satellite networks," European Journal of Operational Research, Elsevier, vol. 219(3), pages 738-750.
    5. Alberto Ceselli & Michael Gatto & Marco E. Lübbecke & Marc Nunkesser & Heiko Schilling, 2008. "Optimizing the Cargo Express Service of Swiss Federal Railways," Transportation Science, INFORMS, vol. 42(4), pages 450-465, November.
    6. Yang Xia & Wenjia Zeng & Xinjie Xing & Yuanzhu Zhan & Kim Hua Tan & Ajay Kumar, 2023. "Joint optimisation of drone routing and battery wear for sustainable supply chain development: a mixed-integer programming model based on blockchain-enabled fleet sharing," Annals of Operations Research, Springer, vol. 327(1), pages 89-127, August.
    7. Baldacci, Roberto & Mingozzi, Aristide & Roberti, Roberto, 2012. "Recent exact algorithms for solving the vehicle routing problem under capacity and time window constraints," European Journal of Operational Research, Elsevier, vol. 218(1), pages 1-6.
    8. Liu, Shixin & Qin, Shujin & Zhang, Ruiyou, 2018. "A branch-and-price algorithm for the multi-trip multi-repairman problem with time windows," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 116(C), pages 25-41.
    9. Roberto Baldacci & Aristide Mingozzi & Roberto Roberti, 2011. "New Route Relaxation and Pricing Strategies for the Vehicle Routing Problem," Operations Research, INFORMS, vol. 59(5), pages 1269-1283, October.
    10. Guy Desaulniers & François Lessard & Ahmed Hadjar, 2008. "Tabu Search, Partial Elementarity, and Generalized k -Path Inequalities for the Vehicle Routing Problem with Time Windows," Transportation Science, INFORMS, vol. 42(3), pages 387-404, August.
    11. Wang, Mengtong & Miao, Lixin & Zhang, Canrong, 2021. "A branch-and-price algorithm for a green location routing problem with multi-type charging infrastructure," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 156(C).
    12. Hernan Caceres & Rajan Batta & Qing He, 2017. "School Bus Routing with Stochastic Demand and Duration Constraints," Transportation Science, INFORMS, vol. 51(4), pages 1349-1364, November.
    13. Yang Xia & Wenjia Zeng & Xinjie Xing & Yuanzhu Zhan & Kim Hua Tan & Ajay Kumar, 2023. "Joint optimisation of drone routing and battery wear for sustainable supply chain development," Post-Print hal-04381308, HAL.
    14. Mads Jepsen & Bjørn Petersen & Simon Spoorendonk & David Pisinger, 2008. "Subset-Row Inequalities Applied to the Vehicle-Routing Problem with Time Windows," Operations Research, INFORMS, vol. 56(2), pages 497-511, April.
    15. Theodore Athanasopoulos & Ioannis Minis, 2013. "Efficient techniques for the multi-period vehicle routing problem with time windows within a branch and price framework," Annals of Operations Research, Springer, vol. 206(1), pages 1-22, July.
    16. Wang, Mengtong & Chen, Shukai & Meng, Qiang, 2024. "Robust safety driver scheduling for autonomous buses," Transportation Research Part B: Methodological, Elsevier, vol. 184(C).

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