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New Branch-and-Cut Algorithm for Bilevel Linear Programming

Author

Listed:
  • C. Audet

    (GERAD and École Polytechnique de Montréal)

  • G. Savard

    (GERAD and École Polytechnique de Montréal)

  • W. Zghal

    (GERAD and École Polytechnique de Montréal)

Abstract

Linear mixed 0–1 integer programming problems may be reformulated as equivalent continuous bilevel linear programming (BLP) problems. We exploit these equivalences to transpose the concept of mixed 0–1 Gomory cuts to BLP. The first phase of our new algorithm generates Gomory-like cuts. The second phase consists of a branch-and-bound procedure to ensure finite termination with a global optimal solution. Different features of the algorithm, in particular, the cut selection and branching criteria are studied in details. We propose also a set of algorithmic tests and procedures to improve the method. Finally, we illustrate the performance through numerical experiments. Our algorithm outperforms pure branch-and-bound when tested on a series of randomly generated problems.

Suggested Citation

  • C. Audet & G. Savard & W. Zghal, 2007. "New Branch-and-Cut Algorithm for Bilevel Linear Programming," Journal of Optimization Theory and Applications, Springer, vol. 134(2), pages 353-370, August.
    • Handle: RePEc:spr:joptap:v:134:y:2007:i:2:d:10.1007_s10957-007-9263-4
    DOI: 10.1007/s10957-007-9263-4
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    References listed on IDEAS

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    1. Wayne F. Bialas & Mark H. Karwan, 1984. "Two-Level Linear Programming," Management Science, INFORMS, vol. 30(8), pages 1004-1020, August.
    2. C. Audet & P. Hansen & B. Jaumard & G. Savard, 1997. "Links Between Linear Bilevel and Mixed 0–1 Programming Problems," Journal of Optimization Theory and Applications, Springer, vol. 93(2), pages 273-300, May.
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    Cited by:

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    2. Joaquim Júdice, 2012. "Algorithms for linear programming with linear complementarity constraints," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(1), pages 4-25, April.
    3. Lizhi Wang, 2013. "Branch-and-bound algorithms for the partial inverse mixed integer linear programming problem," Journal of Global Optimization, Springer, vol. 55(3), pages 491-506, March.
    4. Zhang, Ying & Snyder, Lawrence V. & Ralphs, Ted K. & Xue, Zhaojie, 2016. "The competitive facility location problem under disruption risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 453-473.
    5. M. Hosein Zare & Juan S. Borrero & Bo Zeng & Oleg A. Prokopyev, 2019. "A note on linearized reformulations for a class of bilevel linear integer problems," Annals of Operations Research, Springer, vol. 272(1), pages 99-117, January.
    6. M. Hosein Zare & Osman Y. Özaltın & Oleg A. Prokopyev, 2018. "On a class of bilevel linear mixed-integer programs in adversarial settings," Journal of Global Optimization, Springer, vol. 71(1), pages 91-113, May.
    7. Yohan Shim & Marte Fodstad & Steven Gabriel & Asgeir Tomasgard, 2013. "A branch-and-bound method for discretely-constrained mathematical programs with equilibrium constraints," Annals of Operations Research, Springer, vol. 210(1), pages 5-31, November.
    8. Rahman Khorramfar & Osman Y. Özaltın & Karl G. Kempf & Reha Uzsoy, 2022. "Managing Product Transitions: A Bilevel Programming Approach," INFORMS Journal on Computing, INFORMS, vol. 34(5), pages 2828-2844, September.
    9. Kuo, R.J. & Lee, Y.H. & Zulvia, Ferani E. & Tien, F.C., 2015. "Solving bi-level linear programming problem through hybrid of immune genetic algorithm and particle swarm optimization algorithm," Applied Mathematics and Computation, Elsevier, vol. 266(C), pages 1013-1026.
    10. Yu-Ching Lee & Jong-Shi Pang & John Mitchell, 2015. "An algorithm for global solution to bi-parametric linear complementarity constrained linear programs," Journal of Global Optimization, Springer, vol. 62(2), pages 263-297, June.

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