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Exploiting group symmetry in semidefinite programming relaxations of the quadratic assignment problem

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  • de Klerk, E.

    (Tilburg University, School of Economics and Management)

  • Sotirov, R.

    (Tilburg University, School of Economics and Management)

Abstract

We consider semidefinite programming relaxations of the quadratic assignment problem, and show how to exploit group symmetry in the problem data. Thus we are able to compute the best known lower bounds for several instances of quadratic assignment problems from the problem library: [R.E. Burkard, S.E. Karisch, F. Rendl. QAPLIB — a quadratic assignment problem library. Journal on Global Optimization , 10: 291–403, 1997].
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Suggested Citation

  • de Klerk, E. & Sotirov, R., 2010. "Exploiting group symmetry in semidefinite programming relaxations of the quadratic assignment problem," Other publications TiSEM 73287c80-3bc2-40c4-b02d-4, Tilburg University, School of Economics and Management.
  • Handle: RePEc:tiu:tiutis:73287c80-3bc2-40c4-b02d-452cf88e810a
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    References listed on IDEAS

    as
    1. Ivanov, I.D. & de Klerk, E., 2007. "Parallel Implementation of a Semidefinite Programming Solver based on CSDP in a distributed memory cluster," Other publications TiSEM 9b41ff5e-2808-4d12-a58c-0, Tilburg University, School of Economics and Management.
    2. de Klerk, E. & Maharry, J. & Pasechnik, D.V. & Richter, B. & Salazar, G., 2006. "Improved bounds for the crossing numbers of Km,n and Kn," Other publications TiSEM eca87811-247d-489f-89c2-c, Tilburg University, School of Economics and Management.
    3. Qing Zhao & Stefan E. Karisch & Franz Rendl & Henry Wolkowicz, 1998. "Semidefinite Programming Relaxations for the Quadratic Assignment Problem," Journal of Combinatorial Optimization, Springer, vol. 2(1), pages 71-109, March.
    4. de Klerk, E. & Pasechnik, D.V. & Schrijver, A., 2007. "Reduction of symmetric semidefinite programs using the regular*-representation," Other publications TiSEM e418158e-b9dd-4372-b84c-e, Tilburg University, School of Economics and Management.
    5. Rendl, F. & Sotirov, R., 2007. "Bounds for the quadratic assignment problem using the bundle method," Other publications TiSEM b6d298bc-77c9-4a6d-a043-5, Tilburg University, School of Economics and Management.
    6. Ivanov, I.D. & de Klerk, E., 2007. "Parallel Implementation of a Semidefinite Programming Solver based on CSDP in a distributed memory cluster," Discussion Paper 2007-20, Tilburg University, Center for Economic Research.
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    Citations

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    Cited by:

    1. Hu, Hao & Sotirov, Renata & Wolkowicz, Henry, 2023. "Facial reduction for symmetry reduced semidefinite and doubly nonnegative programs," Other publications TiSEM 8dd3dbae-58fd-4238-b786-e, Tilburg University, School of Economics and Management.
    2. Brosch, Daniel & de Klerk, Etienne, 2021. "Jordan symmetry reduction for conic optimization over the doubly nonnegative cone: Theory and software," Other publications TiSEM 283da78a-b42f-47b4-b2b7-2, Tilburg University, School of Economics and Management.
    3. Matteo Fischetti & Michele Monaci & Domenico Salvagnin, 2012. "Three Ideas for the Quadratic Assignment Problem," Operations Research, INFORMS, vol. 60(4), pages 954-964, August.
    4. Yichuan Ding & Dongdong Ge & Henry Wolkowicz, 2011. "On Equivalence of Semidefinite Relaxations for Quadratic Matrix Programming," Mathematics of Operations Research, INFORMS, vol. 36(1), pages 88-104, February.
    5. Fanz Rendl & Renata Sotirov, 2018. "The min-cut and vertex separator problem," Computational Optimization and Applications, Springer, vol. 69(1), pages 159-187, January.
    6. E. R. van Dam & R. Sotirov, 2015. "On Bounding the Bandwidth of Graphs with Symmetry," INFORMS Journal on Computing, INFORMS, vol. 27(1), pages 75-88, February.
    7. José F. S. Bravo Ferreira & Yuehaw Khoo & Amit Singer, 2018. "Semidefinite programming approach for the quadratic assignment problem with a sparse graph," Computational Optimization and Applications, Springer, vol. 69(3), pages 677-712, April.
    8. Samuel Burer & Sunyoung Kim & Masakazu Kojima, 2014. "Faster, but weaker, relaxations for quadratically constrained quadratic programs," Computational Optimization and Applications, Springer, vol. 59(1), pages 27-45, October.
    9. Xiaolong Kuang & Bissan Ghaddar & Joe Naoum-Sawaya & Luis F. Zuluaga, 2019. "Alternative SDP and SOCP approximations for polynomial optimization," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 7(2), pages 153-175, June.
    10. de Klerk, E. & Pasechnik, D.V. & Sotirov, R., 2008. "On Semidefinite Programming Relaxations of the Traveling Salesman Problem (revision of DP 2007-101)," Other publications TiSEM ea23cd70-a3b1-401a-aa3f-0, Tilburg University, School of Economics and Management.
    11. Feizollahi, Mohammad Javad & Feyzollahi, Hadi, 2015. "Robust quadratic assignment problem with budgeted uncertain flows," Operations Research Perspectives, Elsevier, vol. 2(C), pages 114-123.
    12. de Klerk, E. & Pasechnik, D.V. & Sotirov, R., 2007. "On Semidefinite Programming Relaxations of the Travelling Salesman Problem (Replaced by DP 2008-96)," Other publications TiSEM 12999d3d-956a-4660-9ae4-5, Tilburg University, School of Economics and Management.
    13. E. de Klerk & R. Sotirov & U. Truetsch, 2015. "A New Semidefinite Programming Relaxation for the Quadratic Assignment Problem and Its Computational Perspectives," INFORMS Journal on Computing, INFORMS, vol. 27(2), pages 378-391, May.
    14. Laurent, M., 2009. "Sums of squares, moment matrices and optimization over polynomials," Other publications TiSEM 9fef820b-69d2-43f2-a501-e, Tilburg University, School of Economics and Management.
    15. Nyberg, Axel & Westerlund, Tapio, 2012. "A new exact discrete linear reformulation of the quadratic assignment problem," European Journal of Operational Research, Elsevier, vol. 220(2), pages 314-319.
    16. de Klerk, Etienne & -Nagy, Marianna E. & Sotirov, Renata & Truetsch, Uwe, 2014. "Symmetry in RLT-type relaxations for the quadratic assignment and standard quadratic optimization problems," European Journal of Operational Research, Elsevier, vol. 233(3), pages 488-499.
    17. Jiming Peng & Tao Zhu & Hezhi Luo & Kim-Chuan Toh, 2015. "Semi-definite programming relaxation of quadratic assignment problems based on nonredundant matrix splitting," Computational Optimization and Applications, Springer, vol. 60(1), pages 171-198, January.

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    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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