IDEAS home Printed from https://ideas.repec.org/a/spr/coopap/v59y2014i3p639-665.html
   My bibliography  Save this article

Strong-branching inequalities for convex mixed integer nonlinear programs

Author

Listed:
  • Mustafa Kılınç
  • Jeff Linderoth
  • James Luedtke
  • Andrew Miller

Abstract

Strong branching is an effective branching technique that can significantly reduce the size of the branch-and-bound tree for solving mixed integer nonlinear programming (MINLP) problems. The focus of this paper is to demonstrate how to effectively use “discarded” information from strong branching to strengthen relaxations of MINLP problems. Valid inequalities such as branching-based linearizations, various forms of disjunctive inequalities, and mixing-type inequalities are all discussed. The inequalities span a spectrum from those that require almost no extra effort to compute to those that require the solution of an additional linear program. In the end, we perform an extensive computational study to measure the impact of each of our proposed techniques. Computational results reveal that existing algorithms can be significantly improved by leveraging the information generated as a byproduct of strong branching in the form of valid inequalities. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Mustafa Kılınç & Jeff Linderoth & James Luedtke & Andrew Miller, 2014. "Strong-branching inequalities for convex mixed integer nonlinear programs," Computational Optimization and Applications, Springer, vol. 59(3), pages 639-665, December.
    • Handle: RePEc:spr:coopap:v:59:y:2014:i:3:p:639-665
    DOI: 10.1007/s10589-014-9690-8
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10589-014-9690-8
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10589-014-9690-8?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. Balas, Egon & Jeroslow, Robert G., 1980. "Strengthening cuts for mixed integer programs," European Journal of Operational Research, Elsevier, vol. 4(4), pages 224-234, April.
    2. GÜNLÜK, Oktay & POCHET, Yves, 2001. "Mixing mixed-integer inequalities," LIDAM Reprints CORE 1504, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. POCHET, Yves & WOLSEY, Laurence A., 1993. "Lot-sizing with constant batches: formulation and valid inequalities," LIDAM Reprints CORE 1066, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Samir Elhedhli, 2006. "Service System Design with Immobile Servers, Stochastic Demand, and Congestion," Manufacturing & Service Operations Management, INFORMS, vol. 8(1), pages 92-97, December.
    5. Yves Pochet & Laurence A. Wolsey, 1993. "Lot-Sizing with Constant Batches: Formulation and Valid Inequalities," Mathematics of Operations Research, INFORMS, vol. 18(4), pages 767-785, November.
    6. Atamturk, Alper & Nemhauser, George L. & Savelsbergh, Martin W. P., 2000. "Conflict graphs in solving integer programming problems," European Journal of Operational Research, Elsevier, vol. 121(1), pages 40-55, February.
    7. Egon Balas & Sebastián Ceria & Gérard Cornuéjols, 1996. "Mixed 0-1 Programming by Lift-and-Project in a Branch-and-Cut Framework," Management Science, INFORMS, vol. 42(9), pages 1229-1246, September.
    Full references (including those not matched with items on IDEAS)

    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. Ming Zhao & Minjiao Zhang, 2020. "Multiechelon Lot Sizing: New Complexities and Inequalities," Operations Research, INFORMS, vol. 68(2), pages 534-551, March.
    2. Laurence A. Wolsey, 2002. "Solving Multi-Item Lot-Sizing Problems with an MIP Solver Using Classification and Reformulation," Management Science, INFORMS, vol. 48(12), pages 1587-1602, December.
    3. Mathieu Van Vyve, 2005. "The Continuous Mixing Polyhedron," Mathematics of Operations Research, INFORMS, vol. 30(2), pages 441-452, May.
    4. Akbalik, A. & Pochet, Y., 2009. "Valid inequalities for the single-item capacitated lot sizing problem with step-wise costs," European Journal of Operational Research, Elsevier, vol. 198(2), pages 412-434, October.
    5. Archibald, Thomas W. & Bokkers, Menno B. & Dekker, Rommert & Vliet, Andre van, 1999. "Minimising bins in transmission systems," European Journal of Operational Research, Elsevier, vol. 115(2), pages 380-391, June.
    6. Gaetan Belvaux & Laurence A. Wolsey, 2000. "bc --- prod: A Specialized Branch-and-Cut System for Lot-Sizing Problems," Management Science, INFORMS, vol. 46(5), pages 724-738, May.
    7. van Hoesel, C.P.M. & Wagelmans, A., 1997. "Fully polynomial approximation schemes for single-item capacitated economic lot-sizing problems," Research Memorandum 029, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    8. Miguel Constantino, 1998. "Lower Bounds in Lot-Sizing Models: A Polyhedral Study," Mathematics of Operations Research, INFORMS, vol. 23(1), pages 101-118, February.
    9. Osman Alp & Nesim K. Erkip & Refik Güllü, 2003. "Optimal Lot-Sizing/Vehicle-Dispatching Policies Under Stochastic Lead Times and Stepwise Fixed Costs," Operations Research, INFORMS, vol. 51(1), pages 160-166, February.
    10. Álvaro Porras & Concepción Domínguez & Juan Miguel Morales & Salvador Pineda, 2023. "Tight and Compact Sample Average Approximation for Joint Chance-Constrained Problems with Applications to Optimal Power Flow," INFORMS Journal on Computing, INFORMS, vol. 35(6), pages 1454-1469, November.
    11. Akbalik, Ayse & Penz, Bernard, 2009. "Exact methods for single-item capacitated lot sizing problem with alternative machines and piece-wise linear production costs," International Journal of Production Economics, Elsevier, vol. 119(2), pages 367-379, June.
    12. Hark-Chin Hwang, 2010. "Economic Lot-Sizing for Integrated Production and Transportation," Operations Research, INFORMS, vol. 58(2), pages 428-444, April.
    13. VAN VYVE, Mathieu, 2011. "Linear prices for non-convex electricity markets: models and algorithms," LIDAM Discussion Papers CORE 2011050, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    14. STEPHAN, Rüdiger, 2010. "An extension of disjunctive programming and its impact for compact tree formulations," LIDAM Discussion Papers CORE 2010045, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    15. Chung-Lun Li & Qingying Li, 2016. "Polynomial-Time Solvability of Dynamic Lot Size Problems," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 33(03), pages 1-20, June.
    16. Miller, Andrew J. & Nemhauser, George L. & Savelsbergh, Martin W. P., 2000. "On the capacitated lot-sizing and continuous 0-1 knapsack polyhedra," European Journal of Operational Research, Elsevier, vol. 125(2), pages 298-315, September.
    17. Hark-Chin Hwang, 2009. "Inventory Replenishment and Inbound Shipment Scheduling Under a Minimum Replenishment Policy," Transportation Science, INFORMS, vol. 43(2), pages 244-264, May.
    18. Sebastián Ceria, 2007. "A brief history of lift-and-project," Annals of Operations Research, Springer, vol. 149(1), pages 57-61, February.
    19. BELVAUX, Gaetan & WOLSEY, Laurence A., 2000. "Modelling practical lot-sizing problems as mixed integer programs," LIDAM Discussion Papers CORE 2000009, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    20. Akbalik, Ayse & Rapine, Christophe, 2013. "The single item uncapacitated lot-sizing problem with time-dependent batch sizes: NP-hard and polynomial cases," European Journal of Operational Research, Elsevier, vol. 229(2), pages 353-363.

    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:59:y:2014:i:3:p:639-665. 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.