IDEAS home Printed from https://ideas.repec.org/a/kap/netnom/v12y2011i3p183-207.html
   My bibliography  Save this article

A learning-based variable assignment weighting scheme for heuristic and exact searching in Euclidean traveling salesman problems

Author

Listed:
  • Fan Xue
  • C. Chan
  • W. Ip
  • C. Cheung

Abstract

Many search algorithms have been successfully employed in combinatorial optimization in logistics practice. This paper presents an attempt to weight the variable assignments through supervised learning in subproblems. Heuristic and exact search methods can therefore test promising solutions first. The Euclidean Traveling Salesman Problem (ETSP) is employed as an example to demonstrate the presented method. Analysis shows that the rules can be approximately learned from the training samples from the subproblems and the near optimal tours. Experimental results on large-scale local search tests and small-scale branch-and-bound tests validate the effectiveness of the approach, especially when it is applied to industrial problems. Copyright Springer Science+Business Media, LLC. 2011

Suggested Citation

  • Fan Xue & C. Chan & W. Ip & C. Cheung, 2011. "A learning-based variable assignment weighting scheme for heuristic and exact searching in Euclidean traveling salesman problems," Netnomics, Springer, vol. 12(3), pages 183-207, October.
    • Handle: RePEc:kap:netnom:v:12:y:2011:i:3:p:183-207
    DOI: 10.1007/s11066-011-9064-7
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11066-011-9064-7
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11066-011-9064-7?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. Donald L. Miller & Joseph F. Pekny, 1995. "A Staged Primal-Dual Algorithm for Perfect b-Matching with Edge Capacities," INFORMS Journal on Computing, INFORMS, vol. 7(3), pages 298-320, August.
    2. Jon Jouis Bentley, 1992. "Fast Algorithms for Geometric Traveling Salesman Problems," INFORMS Journal on Computing, INFORMS, vol. 4(4), pages 387-411, November.
    3. Olafsson, Sigurdur & Li, Xiaonan, 2010. "Learning effective new single machine dispatching rules from optimal scheduling data," International Journal of Production Economics, Elsevier, vol. 128(1), pages 118-126, November.
    4. Helsgaun, Keld, 2000. "An effective implementation of the Lin-Kernighan traveling salesman heuristic," European Journal of Operational Research, Elsevier, vol. 126(1), pages 106-130, October.
    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. David Applegate & William Cook & André Rohe, 2003. "Chained Lin-Kernighan for Large Traveling Salesman Problems," INFORMS Journal on Computing, INFORMS, vol. 15(1), pages 82-92, February.
    2. William Cook & André Rohe, 1999. "Computing Minimum-Weight Perfect Matchings," INFORMS Journal on Computing, INFORMS, vol. 11(2), pages 138-148, May.
    3. G Babin & S Deneault & G Laporte, 2007. "Improvements to the Or-opt heuristic for the symmetric travelling salesman problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(3), pages 402-407, March.
    4. Jean Bertrand Gauthier & Stefan Irnich, 2020. "Inter-Depot Moves and Dynamic-Radius Search for Multi-Depot Vehicle Routing Problems," Working Papers 2004, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    5. Jeanette Schmidt & Stefan Irnich, 2020. "New Neighborhoods and an Iterated Local Search Algorithm for the Generalized Traveling Salesman Problem," Working Papers 2020, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    6. Rego, César & Gamboa, Dorabela & Glover, Fred & Osterman, Colin, 2011. "Traveling salesman problem heuristics: Leading methods, implementations and latest advances," European Journal of Operational Research, Elsevier, vol. 211(3), pages 427-441, June.
    7. Anurag Agarwal, 2009. "Theoretical insights into the augmented-neural-network approach for combinatorial optimization," Annals of Operations Research, Springer, vol. 168(1), pages 101-117, April.
    8. Goodson, Justin C. & Ohlmann, Jeffrey W. & Thomas, Barrett W., 2012. "Cyclic-order neighborhoods with application to the vehicle routing problem with stochastic demand," European Journal of Operational Research, Elsevier, vol. 217(2), pages 312-323.
    9. Helena Ramalhinho-Lourenço & Olivier C. Martin & Thomas Stützle, 2000. "Iterated local search," Economics Working Papers 513, Department of Economics and Business, Universitat Pompeu Fabra.
    10. Liqin Huang & Weitian Tong & Randy Goebel & Tian Liu & Guohui Lin, 2015. "A 0.5358-approximation for Bandpass-2," Journal of Combinatorial Optimization, Springer, vol. 30(3), pages 612-626, October.
    11. A. Scholz & G. Wäscher, 2017. "Order Batching and Picker Routing in manual order picking systems: the benefits of integrated routing," 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. 25(2), pages 491-520, June.
    12. Luca Maria Gambardella & Marco Dorigo, 2000. "An Ant Colony System Hybridized with a New Local Search for the Sequential Ordering Problem," INFORMS Journal on Computing, INFORMS, vol. 12(3), pages 237-255, August.
    13. Kusum Deep & Hadush Mebrahtu & Atulya K. Nagar, 2018. "Novel GA for metropolitan stations of Indian railways when modelled as a TSP," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 9(3), pages 639-645, June.
    14. Lang, Jan Christian & Shen, Zuo-Jun Max, 2011. "Fix-and-optimize heuristics for capacitated lot-sizing with sequence-dependent setups and substitutions," European Journal of Operational Research, Elsevier, vol. 214(3), pages 595-605, November.
    15. Löhndorf, Nils & Riel, Manuel & Minner, Stefan, 2014. "Simulation optimization for the stochastic economic lot scheduling problem with sequence-dependent setup times," International Journal of Production Economics, Elsevier, vol. 157(C), pages 170-176.
    16. van Gils, Teun & Ramaekers, Katrien & Braekers, Kris & Depaire, Benoît & Caris, An, 2018. "Increasing order picking efficiency by integrating storage, batching, zone picking, and routing policy decisions," International Journal of Production Economics, Elsevier, vol. 197(C), pages 243-261.
    17. Ghosh, Diptesh, 2016. "Exploring Lin Kernighan neighborhoods for the indexing problem," IIMA Working Papers WP2016-02-13, Indian Institute of Management Ahmedabad, Research and Publication Department.
    18. Drexl, M. & Schneider, M., 2014. "A Survey of the Standard Location-Routing Problem," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 65940, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    19. Silva, Allyson & Coelho, Leandro C. & Darvish, Maryam & Renaud, Jacques, 2020. "Integrating storage location and order picking problems in warehouse planning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).
    20. B. I. Goldengorin & D. S. Malyshev & P. M. Pardalos & V. A. Zamaraev, 2015. "A tolerance-based heuristic approach for the weighted independent set problem," Journal of Combinatorial Optimization, Springer, vol. 29(2), pages 433-450, February.

    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:kap:netnom:v:12:y:2011:i:3:p:183-207. 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.