IDEAS home Printed from https://ideas.repec.org/a/pal/jorsoc/v62y2011i11d10.1057_jors.2010.165.html
   My bibliography  Save this article

Set partitioning and packing versus assignment formulations for subassembly matching problems

Author

Listed:
  • A Ghoniem

    (University of Massachusetts Amherst)

  • H D Sherali

    (Virginia Polytechnic Institute and State University)

Abstract

This paper addresses alternative formulations and model enhancements for two combinatorial optimization problems that arise in subassembly matching problems. The first problem seeks to minimize the total deviation in certain quality characteristics for the resulting final products from a vector of target values, whereas the second aims at maximizing the throughput under specified tolerance restrictions. We propose set partitioning and packing models in concert with a specialized column generation (CG) procedure that significantly outperform alternative assignment-based formulations presented in the literature, even when the latter are enhanced via tailored symmetry-defeating strategies. In particular, we emphasize the critical importance of incorporating a complementary CG feature to consistently produce near-optimal solutions to the proposed set partitioning and packing models. Extensive computational results are presented to demonstrate the relative effectiveness of the different proposed modelling and algorithmic strategies.

Suggested Citation

  • A Ghoniem & H D Sherali, 2011. "Set partitioning and packing versus assignment formulations for subassembly matching problems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(11), pages 2023-2033, November.
    • Handle: RePEc:pal:jorsoc:v:62:y:2011:i:11:d:10.1057_jors.2010.165
    DOI: 10.1057/jors.2010.165
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/jors.2010.165
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/jors.2010.165?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. WOLSEY, Laurence A., 2003. "Strong formulations for mixed integer programs: valid inequalities and extended formulations," LIDAM Reprints CORE 1627, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Cynthia Barnhart & Ellis L. Johnson & George L. Nemhauser & Martin W. P. Savelsbergh & Pamela H. Vance, 1998. "Branch-and-Price: Column Generation for Solving Huge Integer Programs," Operations Research, INFORMS, vol. 46(3), pages 316-329, June.
    3. Hanif D. Sherali & J. Cole Smith, 2001. "Improving Discrete Model Representations via Symmetry Considerations," Management Science, INFORMS, vol. 47(10), pages 1396-1407, October.
    4. Marco E. Lübbecke & Jacques Desrosiers, 2005. "Selected Topics in Column Generation," Operations Research, INFORMS, vol. 53(6), pages 1007-1023, December.
    5. WOLSEY, Laurence A., 1989. "Strong formulations for mixed integer programming: a survey," LIDAM Reprints CORE 864, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. C.R. Coullard & A.B. Gamble & P.C. Jones, 1998. "Matching problems in selective assembly operations," Annals of Operations Research, Springer, vol. 76(0), pages 95-107, January.
    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. Isabel Martins & Filipe Alvelos & Miguel Constantino, 2012. "A branch-and-price approach for harvest scheduling subject to maximum area restrictions," Computational Optimization and Applications, Springer, vol. 51(1), pages 363-385, January.
    2. Omid Shahvari & Rasaratnam Logendran & Madjid Tavana, 2022. "An efficient model-based branch-and-price algorithm for unrelated-parallel machine batching and scheduling problems," Journal of Scheduling, Springer, vol. 25(5), pages 589-621, October.
    3. Melanie Erhard, 2021. "Flexible staffing of physicians with column generation," Flexible Services and Manufacturing Journal, Springer, vol. 33(1), pages 212-252, March.
    4. Miriam Kießling & Sascha Kurz & Jörg Rambau, 2021. "An exact column-generation approach for the lot-type design problem," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(3), pages 741-780, October.
    5. Melchiori, Anna & Sgalambro, Antonino, 2020. "A branch and price algorithm to solve the Quickest Multicommodity k-splittable Flow Problem," European Journal of Operational Research, Elsevier, vol. 282(3), pages 846-857.
    6. Renaud Chicoisne, 2023. "Computational aspects of column generation for nonlinear and conic optimization: classical and linearized schemes," Computational Optimization and Applications, Springer, vol. 84(3), pages 789-831, April.
    7. Shen, Yunzhuang & Sun, Yuan & Li, Xiaodong & Eberhard, Andrew & Ernst, Andreas, 2023. "Adaptive solution prediction for combinatorial optimization," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1392-1408.
    8. Rigo, Cezar Antônio & Seman, Laio Oriel & Camponogara, Eduardo & Morsch Filho, Edemar & Bezerra, Eduardo Augusto & Munari, Pedro, 2022. "A branch-and-price algorithm for nanosatellite task scheduling to improve mission quality-of-service," European Journal of Operational Research, Elsevier, vol. 303(1), pages 168-183.
    9. Ali, Agha Iqbal & O'Connor, Debra J., 2010. "The impact of distribution system characteristics on computational tractability," European Journal of Operational Research, Elsevier, vol. 200(2), pages 323-333, January.
    10. Range, Troels Martin & Kozlowski, Dawid & Petersen, Niels Chr., 2019. "Dynamic job assignment: A column generation approach with an application to surgery allocation," European Journal of Operational Research, Elsevier, vol. 272(1), pages 78-93.
    11. Yael Grushka-Cockayne & Bert De Reyck & Zeger Degraeve, 2008. "An Integrated Decision-Making Approach for Improving European Air Traffic Management," Management Science, INFORMS, vol. 54(8), pages 1395-1409, August.
    12. Guy Desaulniers & Diego Pecin & Claudio Contardo, 2019. "Selective pricing in branch-price-and-cut algorithms for vehicle routing," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 8(2), pages 147-168, June.
    13. Walteros, Jose L. & Vogiatzis, Chrysafis & Pasiliao, Eduardo L. & Pardalos, Panos M., 2014. "Integer programming models for the multidimensional assignment problem with star costs," European Journal of Operational Research, Elsevier, vol. 235(3), pages 553-568.
    14. Luciano Costa & Claudio Contardo & Guy Desaulniers, 2019. "Exact Branch-Price-and-Cut Algorithms for Vehicle Routing," Transportation Science, INFORMS, vol. 53(4), pages 946-985, July.
    15. Jiliu Li & Zhixing Luo & Roberto Baldacci & Hu Qin & Zhou Xu, 2023. "A New Exact Algorithm for Single-Commodity Vehicle Routing with Split Pickups and Deliveries," INFORMS Journal on Computing, INFORMS, vol. 35(1), pages 31-49, January.
    16. Fink, Martin & Desaulniers, Guy & Frey, Markus & Kiermaier, Ferdinand & Kolisch, Rainer & Soumis, François, 2019. "Column generation for vehicle routing problems with multiple synchronization constraints," European Journal of Operational Research, Elsevier, vol. 272(2), pages 699-711.
    17. Rauchecker, Gerhard & Schryen, Guido, 2019. "An exact branch-and-price algorithm for scheduling rescue units during disaster response," European Journal of Operational Research, Elsevier, vol. 272(1), pages 352-363.
    18. Jardar Andersen & Marielle Christiansen & Teodor Gabriel Crainic & Roar Grønhaug, 2011. "Branch and Price for Service Network Design with Asset Management Constraints," Transportation Science, INFORMS, vol. 45(1), pages 33-49, February.
    19. Timo Gschwind & Stefan Irnich, 2014. "Dual Inequalities for Stabilized Column Generation Revisited," Working Papers 1407, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz, revised 23 Jul 2014.
    20. Václavík, Roman & Novák, Antonín & Šůcha, Přemysl & Hanzálek, Zdeněk, 2018. "Accelerating the Branch-and-Price Algorithm Using Machine Learning," European Journal of Operational Research, Elsevier, vol. 271(3), pages 1055-1069.

    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:pal:jorsoc:v:62:y:2011:i:11:d:10.1057_jors.2010.165. 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.palgrave-journals.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.