IDEAS home Printed from https://ideas.repec.org/a/pal/jorsoc/v59y2008i3d10.1057_palgrave.jors.2602356.html
   My bibliography  Save this article

VLSN search algorithms for partitioning problems using matching neighbourhoods

Author

Listed:
  • T Öncan

    (Galatasaray Üniversitesi)

  • S N Kabadi

    (University of New Brunswick)

  • K P K Nair

    (University of New Brunswick)

  • A P Punnen

    (Simon Fraser University Surrey)

Abstract

In this paper, we propose a general paradigm to design very large-scale neighbourhood search algorithms for generic partitioning-type problems. We identify neighbourhoods of exponential size, called matching neighbourhoods, comprised of the union of a class of exponential neighbourhoods. It is shown that these individual components of the matching neighbourhood can be searched in polynomial time, whereas searching the matching neighbourhood is NP-hard. Matching neighbourhood subsumes a well-known class of exponential neighbourhoods called cyclic-exchange neighbourhoods. Our VLSN algorithm is implemented for two special cases of the partitioning problem; the covering assignment problem and the single source transportation problem. Encouraging experimental results are also reported.

Suggested Citation

  • T Öncan & S N Kabadi & K P K Nair & A P Punnen, 2008. "VLSN search algorithms for partitioning problems using matching neighbourhoods," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(3), pages 388-398, March.
    • Handle: RePEc:pal:jorsoc:v:59:y:2008:i:3:d:10.1057_palgrave.jors.2602356
    DOI: 10.1057/palgrave.jors.2602356
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/palgrave.jors.2602356
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/palgrave.jors.2602356?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. V. Srinivasan & G. L. Thompson, 1973. "An Algorithm for Assigning Uses to Sources in a Special Class of Transportation Problems," Operations Research, INFORMS, vol. 21(1), pages 284-295, February.
    2. Ravindra K. Ahuja & Krishna C. Jha & James B. Orlin & Dushyant Sharma, 2007. "Very Large-Scale Neighborhood Search for the Quadratic Assignment Problem," INFORMS Journal on Computing, INFORMS, vol. 19(4), pages 646-657, November.
    3. Paul M. Thompson & Harilaos N. Psaraftis, 1993. "Cyclic Transfer Algorithm for Multivehicle Routing and Scheduling Problems," Operations Research, INFORMS, vol. 41(5), pages 935-946, October.
    4. Orlin, James & Punnen, Abraham & Schulz, Andreas, 2004. "Approximate Local Search in Combinatorial Optimization," Working papers 4325-03, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    5. L.R. Foulds & J.M. Wilson, 1997. "A variation of the generalized assignment problem arising in the New Zealand dairy industry," Annals of Operations Research, Springer, vol. 69(0), pages 105-114, January.
    6. Adriano De Maio & Claudio Roveda, 1971. "An all Zero-One Algorithm for a Certain Class of Transportation Problems," Operations Research, INFORMS, vol. 19(6), pages 1406-1418, October.
    7. Karla L. Hoffman & Manfred Padberg, 1993. "Solving Airline Crew Scheduling Problems by Branch-and-Cut," Management Science, INFORMS, vol. 39(6), pages 657-682, June.
    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. A Awasthi & S S Chauhan & M Parent & Jean-Marie Proth, 2010. "Algorithms for partitioning of large routing networks," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(7), pages 1159-1167, July.

    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. Pisut Pongchairerks, 2023. "A Probabilistic Hill-Climbing Algorithm for the Single-Source Transportation Problem," Sustainability, MDPI, vol. 15(5), pages 1-14, February.
    2. Maenhout, Broos & Vanhoucke, Mario, 2010. "A hybrid scatter search heuristic for personalized crew rostering in the airline industry," European Journal of Operational Research, Elsevier, vol. 206(1), pages 155-167, October.
    3. Sriram, Chellappan & Haghani, Ali, 2003. "An optimization model for aircraft maintenance scheduling and re-assignment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(1), pages 29-48, January.
    4. Rossi, Fabrizio & Smriglio, Stefano, 2001. "A set packing model for the ground holding problem in congested networks," European Journal of Operational Research, Elsevier, vol. 131(2), pages 400-416, June.
    5. Erwin Abbink & Matteo Fischetti & Leo Kroon & Gerrit Timmer & Michiel Vromans, 2005. "Reinventing Crew Scheduling at Netherlands Railways," Interfaces, INFORMS, vol. 35(5), pages 393-401, October.
    6. Liu, Fuh-Hwa Franklin & Shen, Sheng-Yuan, 1999. "A route-neighborhood-based metaheuristic for vehicle routing problem with time windows," European Journal of Operational Research, Elsevier, vol. 118(3), pages 485-504, November.
    7. Drexl, Andreas & Nissen, Rudiger & Patterson, James H. & Salewski, Frank, 2000. "ProGen/[pi]x - An instance generator for resource-constrained project scheduling problems with partially renewable resources and further extensions," European Journal of Operational Research, Elsevier, vol. 125(1), pages 59-72, August.
    8. Andreas Stenger & Daniele Vigo & Steffen Enz & Michael Schwind, 2013. "An Adaptive Variable Neighborhood Search Algorithm for a Vehicle Routing Problem Arising in Small Package Shipping," Transportation Science, INFORMS, vol. 47(1), pages 64-80, February.
    9. Masoud Yaghini & Mohammad Karimi & Mohadeseh Rahbar, 2015. "A set covering approach for multi-depot train driver scheduling," Journal of Combinatorial Optimization, Springer, vol. 29(3), pages 636-654, April.
    10. Martin Durbin & Karla Hoffman, 2008. "OR PRACTICE---The Dance of the Thirty-Ton Trucks: Dispatching and Scheduling in a Dynamic Environment," Operations Research, INFORMS, vol. 56(1), pages 3-19, February.
    11. Michael J. Brusco & Larry W. Jacobs, 2000. "Optimal Models for Meal-Break and Start-Time Flexibility in Continuous Tour Scheduling," Management Science, INFORMS, vol. 46(12), pages 1630-1641, December.
    12. Zwaneveld, Peter J. & Kroon, Leo G. & van Hoesel, Stan P. M., 2001. "Routing trains through a railway station based on a node packing model," European Journal of Operational Research, Elsevier, vol. 128(1), pages 14-33, January.
    13. Xu, Yifan & Wandelt, Sebastian & Sun, Xiaoqian, 2021. "Airline integrated robust scheduling with a variable neighborhood search based heuristic," Transportation Research Part B: Methodological, Elsevier, vol. 149(C), pages 181-203.
    14. Panta Lučić & Dušan Teodorović, 2007. "Metaheuristics approach to the aircrew rostering problem," Annals of Operations Research, Springer, vol. 155(1), pages 311-338, November.
    15. Darby-Dowman, K. & Fink, R. K. & Mitra, G. & Smith, J. W., 1995. "An intelligent system for US Coast Guard cutter scheduling," European Journal of Operational Research, Elsevier, vol. 87(3), pages 574-585, December.
    16. Abbink, E.J.W., 2008. "Solving large scale crew scheduling problems by using iterative partitioning," Econometric Institute Research Papers EI 2008-03, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    17. Lagerholm, Martin & Peterson, Carsten & Soderberg, Bo, 2000. "Airline crew scheduling using Potts mean field techniques," European Journal of Operational Research, Elsevier, vol. 120(1), pages 81-96, January.
    18. Gerald G. Brown & Robert F. Dell & Ray L. Davis & Richard H. Duff, 2002. "Optimizing Plant-Line Schedules and an Application at Hidden Valley Manufacturing Company," Interfaces, INFORMS, vol. 32(3), pages 1-14, June.
    19. Marco Antonio Boschetti & Vittorio Maniezzo, 2022. "Matheuristics: using mathematics for heuristic design," 4OR, Springer, vol. 20(2), pages 173-208, June.
    20. Michael Jünger & Sven Mallach, 2021. "Exact Facetial Odd-Cycle Separation for Maximum Cut and Binary Quadratic Optimization," INFORMS Journal on Computing, INFORMS, vol. 33(4), pages 1419-1430, October.

    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:59:y:2008:i:3:d:10.1057_palgrave.jors.2602356. 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.