IDEAS home Printed from https://ideas.repec.org/a/spr/mathme/v76y2012i1p67-93.html
   My bibliography  Save this article

Could we use a million cores to solve an integer program?

Author

Listed:
  • Thorsten Koch
  • Ted Ralphs
  • Yuji Shinano

Abstract

Given the steady increase in cores per CPU, it is only a matter of time before supercomputers will have a million or more cores. In this article, we investigate the opportunities and challenges that will arise when trying to utilize this vast computing power to solve a single integer linear optimization problem. We also raise the question of whether best practices in sequential solution of ILPs will be effective in massively parallel environments. Copyright Springer-Verlag 2012

Suggested Citation

  • Thorsten Koch & Ted Ralphs & Yuji Shinano, 2012. "Could we use a million cores to solve an integer program?," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 76(1), pages 67-93, August.
    • Handle: RePEc:spr:mathme:v:76:y:2012:i:1:p:67-93
    DOI: 10.1007/s00186-012-0390-9
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s00186-012-0390-9
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s00186-012-0390-9?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. Osman Y. Özaltın & Brady Hunsaker & Andrew J. Schaefer, 2011. "Predicting the Solution Time of Branch-and-Bound Algorithms for Mixed-Integer Programs," INFORMS Journal on Computing, INFORMS, vol. 23(3), pages 392-403, August.
    2. Marshall L. Fisher, 2004. "The Lagrangian Relaxation Method for Solving Integer Programming Problems," Management Science, INFORMS, vol. 50(12_supple), pages 1861-1871, December.
    3. Gérard Cornuéjols & Miroslav Karamanov & Yanjun Li, 2006. "Early Estimates of the Size of Branch-and-Bound Trees," INFORMS Journal on Computing, INFORMS, vol. 18(1), pages 86-96, February.
    4. William Cook & Thomas Rutherford & Herbert E. Scarf & David Shallcross, 1993. "An Implementation of the Generalized Basis Reduction Algorithm for Integer Programming," INFORMS Journal on Computing, INFORMS, vol. 5(2), pages 206-212, May.
    5. Robert E. Bixby, 2002. "Solving Real-World Linear Programs: A Decade and More of Progress," Operations Research, INFORMS, vol. 50(1), pages 3-15, February.
    6. Y. Xu & T. K. Ralphs & L. Ladányi & M. J. Saltzman, 2009. "Computational Experience with a Software Framework for Parallel Integer Programming," INFORMS Journal on Computing, INFORMS, vol. 21(3), pages 383-397, August.
    7. AARDAL, Karen & WEISMANTEL, Robert & WOLSEY, Laurence, 2002. "Non-standard approaches to integer programming," LIDAM Reprints CORE 1568, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. 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.
    9. Marshall L. Fisher, 2004. "Comments on ÜThe Lagrangian Relaxation Method for Solving Integer Programming ProblemsÝ," Management Science, INFORMS, vol. 50(12_supple), pages 1872-1874, December.
    10. 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.
    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. Yuji Shinano & Stefan Heinz & Stefan Vigerske & Michael Winkler, 2018. "FiberSCIP—A Shared Memory Parallelization of SCIP," INFORMS Journal on Computing, INFORMS, vol. 30(1), pages 11-30, February.
    2. Lluís-Miquel Munguía & Shabbir Ahmed & David A. Bader & George L. Nemhauser & Yufen Shao, 2018. "Alternating criteria search: a parallel large neighborhood search algorithm for mixed integer programs," Computational Optimization and Applications, Springer, vol. 69(1), pages 1-24, January.
    3. Ivo Nowak & Norman Breitfeld & Eligius M. T. Hendrix & Grégoire Njacheun-Njanzoua, 2018. "Decomposition-based Inner- and Outer-Refinement Algorithms for Global Optimization," Journal of Global Optimization, Springer, vol. 72(2), pages 305-321, October.
    4. Timo Berthold, 2018. "A computational study of primal heuristics inside an MI(NL)P solver," Journal of Global Optimization, Springer, vol. 70(1), pages 189-206, January.
    5. Luke Mason & Vicky Mak-Hau & Andreas Ernst, 2015. "A parallel optimisation approach for the realisation problem in intensity modulated radiotherapy treatment planning," Computational Optimization and Applications, Springer, vol. 60(2), pages 441-477, March.
    6. Lluís-Miquel Munguía & Geoffrey Oxberry & Deepak Rajan & Yuji Shinano, 2019. "Parallel PIPS-SBB: multi-level parallelism for stochastic mixed-integer programs," Computational Optimization and Applications, Springer, vol. 73(2), pages 575-601, June.
    7. Matteo Fischetti & Michele Monaci, 2014. "Exploiting Erraticism in Search," Operations Research, INFORMS, vol. 62(1), pages 114-122, February.
    8. Martin Branda, 2013. "On relations between chance constrained and penalty function problems under discrete distributions," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 77(2), pages 265-277, April.

    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. Yanling Chu & Xiaoju Zhang & Zhongzhen Yang, 2017. "Multiple quay cranes scheduling for double cycling in container terminals," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-19, July.
    2. José Berenguel & L. Casado & I. García & Eligius Hendrix, 2013. "On estimating workload in interval branch-and-bound global optimization algorithms," Journal of Global Optimization, Springer, vol. 56(3), pages 821-844, July.
    3. An, Yu & Zhang, Yu & Zeng, Bo, 2015. "The reliable hub-and-spoke design problem: Models and algorithms," Transportation Research Part B: Methodological, Elsevier, vol. 77(C), pages 103-122.
    4. Dollevoet, Twan & van Essen, J. Theresia & Glorie, Kristiaan M., 2018. "Solution methods for the tray optimization problem," European Journal of Operational Research, Elsevier, vol. 271(3), pages 1070-1084.
    5. Alexandre Belloni & Mitchell J. Lovett & William Boulding & Richard Staelin, 2012. "Optimal Admission and Scholarship Decisions: Choosing Customized Marketing Offers to Attract a Desirable Mix of Customers," Marketing Science, INFORMS, vol. 31(4), pages 621-636, July.
    6. Zhizhu Lai & Qun Yue & Zheng Wang & Dongmei Ge & Yulong Chen & Zhihong Zhou, 2022. "The min-p robust optimization approach for facility location problem under uncertainty," Journal of Combinatorial Optimization, Springer, vol. 44(2), pages 1134-1160, September.
    7. Yokoya, Daisuke & Duin, Cees W. & Yamada, Takeo, 2011. "A reduction approach to the repeated assignment problem," European Journal of Operational Research, Elsevier, vol. 210(2), pages 185-193, April.
    8. Zhang, Zheng & Wei, Yongqi & Xiong, Youming & Peng, Geng & Wang, Guorong & Lu, Jingsheng & Zhong, Lin & Wang, Jingpeng, 2022. "Influence of the location of drilling fluid loss on wellbore temperature distribution during drilling," Energy, Elsevier, vol. 244(PB).
    9. Jabbarzadeh, Armin & Fahimnia, Behnam & Sheu, Jiuh-Biing & Moghadam, Hani Shahmoradi, 2016. "Designing a supply chain resilient to major disruptions and supply/demand interruptions," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 121-149.
    10. Junming Liu & Weiwei Chen & Jingyuan Yang & Hui Xiong & Can Chen, 2022. "Iterative Prediction-and-Optimization for E-Logistics Distribution Network Design," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 769-789, March.
    11. Springborn, Michael R., 2014. "Risk aversion and adaptive management: Insights from a multi-armed bandit model of invasive species risk," Journal of Environmental Economics and Management, Elsevier, vol. 68(2), pages 226-242.
    12. Li, Wenjie & Yang, Lixing & Wang, Li & Zhou, Xuesong & Liu, Ronghui & Gao, Ziyou, 2017. "Eco-reliable path finding in time-variant and stochastic networks," Energy, Elsevier, vol. 121(C), pages 372-387.
    13. Zheng, Jianfeng & Meng, Qiang & Sun, Zhuo, 2014. "Impact analysis of maritime cabotage legislations on liner hub-and-spoke shipping network design," European Journal of Operational Research, Elsevier, vol. 234(3), pages 874-884.
    14. Vasile BRÄ‚TIAN, 2018. "Portfolio Optimization. Application of the Markowitz Model Using Lagrange and Profitability Forecast," Expert Journal of Economics, Sprint Investify, vol. 6(1), pages 26-34.
    15. Miguel A. Lejeune & John Turner, 2019. "Planning Online Advertising Using Gini Indices," Operations Research, INFORMS, vol. 67(5), pages 1222-1245, September.
    16. Claudio Gambella & Joe Naoum-Sawaya & Bissan Ghaddar, 2018. "The Vehicle Routing Problem with Floating Targets: Formulation and Solution Approaches," INFORMS Journal on Computing, INFORMS, vol. 30(3), pages 554-569, August.
    17. Xie, Siyang & An, Kun & Ouyang, Yanfeng, 2019. "Planning facility location under generally correlated facility disruptions: Use of supporting stations and quasi-probabilities," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 115-139.
    18. Samadi, Mohammadreza & Nikolaev, Alexander & Nagi, Rakesh, 2016. "A subjective evidence model for influence maximization in social networks," Omega, Elsevier, vol. 59(PB), pages 263-278.
    19. Zhang, Zhi-Hai & Jiang, Hai & Pan, Xunzhang, 2012. "A Lagrangian relaxation based approach for the capacitated lot sizing problem in closed-loop supply chain," International Journal of Production Economics, Elsevier, vol. 140(1), pages 249-255.
    20. Wang, Julong & Liu, Zhixue & Li, Feng, 2024. "Integrated production and transportation scheduling problem under nonlinear cost structures," European Journal of Operational Research, Elsevier, vol. 313(3), pages 883-904.

    More about this item

    Keywords

    Integer programming; Parallelization;

    Statistics

    Access and download statistics

    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:mathme:v:76:y:2012:i:1:p:67-93. 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.