IDEAS home Printed from https://ideas.repec.org/a/spr/coopap/v43y2009i2p181-195.html
   My bibliography  Save this article

Globally solving box-constrained nonconvex quadratic programs with semidefinite-based finite branch-and-bound

Author

Listed:
  • Samuel Burer
  • Dieter Vandenbussche

Abstract

No abstract is available for this item.

Suggested Citation

  • Samuel Burer & Dieter Vandenbussche, 2009. "Globally solving box-constrained nonconvex quadratic programs with semidefinite-based finite branch-and-bound," Computational Optimization and Applications, Springer, vol. 43(2), pages 181-195, June.
    • Handle: RePEc:spr:coopap:v:43:y:2009:i:2:p:181-195
    DOI: 10.1007/s10589-007-9137-6
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10589-007-9137-6
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10589-007-9137-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Pierre Hansen & Brigitte Jaumard & MichèLe Ruiz & Junjie Xiong, 1993. "Global minimization of indefinite quadratic functions subject to box constraints," Naval Research Logistics (NRL), John Wiley & Sons, vol. 40(3), pages 373-392, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hanif Sherali & Evrim Dalkiran & Jitamitra Desai, 2012. "Enhancing RLT-based relaxations for polynomial programming problems via a new class of v-semidefinite cuts," Computational Optimization and Applications, Springer, vol. 52(2), pages 483-506, June.
    2. Jiao, Hongwei & Liu, Sanyang & Lu, Nan, 2015. "A parametric linear relaxation algorithm for globally solving nonconvex quadratic programming," Applied Mathematics and Computation, Elsevier, vol. 250(C), pages 973-985.
    3. Christoph Buchheim & Maribel Montenegro & Angelika Wiegele, 2019. "SDP-based branch-and-bound for non-convex quadratic integer optimization," Journal of Global Optimization, Springer, vol. 73(3), pages 485-514, March.
    4. Edirisinghe, Chanaka & Jeong, Jaehwan & Chen, Jingnan, 2021. "Optimal portfolio deleveraging under market impact and margin restrictions," European Journal of Operational Research, Elsevier, vol. 294(2), pages 746-759.
    5. Yash Puranik & Nikolaos V. Sahinidis, 2017. "Bounds tightening based on optimality conditions for nonconvex box-constrained optimization," Journal of Global Optimization, Springer, vol. 67(1), pages 59-77, January.
    6. Sven de Vries & Bernd Perscheid, 2022. "Tight compact extended relaxations for nonconvex quadratic programming problems with box constraints," Journal of Global Optimization, Springer, vol. 84(3), pages 591-606, November.
    7. Huixian Wu & Hezhi Luo & Xianye Zhang & Haiqiang Qi, 2023. "An effective global algorithm for worst-case linear optimization under polyhedral uncertainty," Journal of Global Optimization, Springer, vol. 87(1), pages 191-219, September.
    8. Wei Xia & Juan C. Vera & Luis F. Zuluaga, 2020. "Globally Solving Nonconvex Quadratic Programs via Linear Integer Programming Techniques," INFORMS Journal on Computing, INFORMS, vol. 32(1), pages 40-56, January.
    9. X. J. Zheng & X. L. Sun & D. Li, 2010. "Separable Relaxation for Nonconvex Quadratic Integer Programming: Integer Diagonalization Approach," Journal of Optimization Theory and Applications, Springer, vol. 146(2), pages 463-489, August.
    10. Hezhi Luo & Yuanyuan Chen & Xianye Zhang & Duan Li & Huixian Wu, 2020. "Effective Algorithms for Optimal Portfolio Deleveraging Problem with Cross Impact," Papers 2012.07368, arXiv.org, revised Jan 2021.
    11. Hezhi Luo & Xiaodong Ding & Jiming Peng & Rujun Jiang & Duan Li, 2021. "Complexity Results and Effective Algorithms for Worst-Case Linear Optimization Under Uncertainties," INFORMS Journal on Computing, INFORMS, vol. 33(1), pages 180-197, January.
    12. Xiaodong Ding & Hezhi Luo & Huixian Wu & Jianzhen Liu, 2021. "An efficient global algorithm for worst-case linear optimization under uncertainties based on nonlinear semidefinite relaxation," Computational Optimization and Applications, Springer, vol. 80(1), pages 89-120, September.
    13. Hezhi Luo & Xianye Zhang & Huixian Wu & Weiqiang Xu, 2023. "Effective algorithms for separable nonconvex quadratic programming with one quadratic and box constraints," Computational Optimization and Applications, Springer, vol. 86(1), pages 199-240, September.
    14. Xiaoli Cen & Yong Xia, 2021. "A New Global Optimization Scheme for Quadratic Programs with Low-Rank Nonconvexity," INFORMS Journal on Computing, INFORMS, vol. 33(4), pages 1368-1383, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wei Xia & Juan C. Vera & Luis F. Zuluaga, 2020. "Globally Solving Nonconvex Quadratic Programs via Linear Integer Programming Techniques," INFORMS Journal on Computing, INFORMS, vol. 32(1), pages 40-56, January.
    2. Benjamin Beach & Robert Hildebrand & Joey Huchette, 2022. "Compact mixed-integer programming formulations in quadratic optimization," Journal of Global Optimization, Springer, vol. 84(4), pages 869-912, December.
    3. Yash Puranik & Nikolaos V. Sahinidis, 2017. "Bounds tightening based on optimality conditions for nonconvex box-constrained optimization," Journal of Global Optimization, Springer, vol. 67(1), pages 59-77, January.
    4. Riccardo Cambini & Claudio Sodini, 2008. "A computational comparison of some branch and bound methods for indefinite quadratic programs," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 16(2), pages 139-152, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:coopap:v:43:y:2009:i:2:p:181-195. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.