IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v199y1993i2p232-242.html
   My bibliography  Save this article

A fast optimization method based on a hierarchical strategy for the travelling salesman problem

Author

Listed:
  • Sun, T.
  • Meakin, P.
  • Jøssang, T.

Abstract

An algorithm based on a hierarchical strategy is proposed for solving the travelling salesman problem. The tour patterns have been analyzed and compared with those generated from different stages of simulated annealing. A set of problems with known solutions has been used to evaluate the new algorithm. The hierarchical algorithm is shown to be very fast. It finds a path length similar to that obtained using simulated annealing algorithm. The path length is quite far from the global minimum but compares favorably to that obtained using simulated annealing.

Suggested Citation

  • Sun, T. & Meakin, P. & Jøssang, T., 1993. "A fast optimization method based on a hierarchical strategy for the travelling salesman problem," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 199(2), pages 232-242.
  • Handle: RePEc:eee:phsmap:v:199:y:1993:i:2:p:232-242
    DOI: 10.1016/0378-4371(93)90004-N
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/037843719390004N
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/0378-4371(93)90004-N?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. S. Lin & B. W. Kernighan, 1973. "An Effective Heuristic Algorithm for the Traveling-Salesman Problem," Operations Research, INFORMS, vol. 21(2), pages 498-516, April.
    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. Mutsunori Yagiura & Toshihide Ibaraki & Fred Glover, 2004. "An Ejection Chain Approach for the Generalized Assignment Problem," INFORMS Journal on Computing, INFORMS, vol. 16(2), pages 133-151, May.
    2. Zi-bin Jiang & Qiong Yang, 2016. "A Discrete Fruit Fly Optimization Algorithm for the Traveling Salesman Problem," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-15, November.
    3. Stefan Poikonen & Bruce Golden, 2020. "The Mothership and Drone Routing Problem," INFORMS Journal on Computing, INFORMS, vol. 32(2), pages 249-262, April.
    4. 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.
    5. Rego, Cesar & Roucairol, Catherine, 1995. "Using Tabu search for solving a dynamic multi-terminal truck dispatching problem," European Journal of Operational Research, Elsevier, vol. 83(2), pages 411-429, June.
    6. Wayne Desarbo, 1982. "Gennclus: New models for general nonhierarchical clustering analysis," Psychometrika, Springer;The Psychometric Society, vol. 47(4), pages 449-475, December.
    7. E A Silver, 2004. "An overview of heuristic solution methods," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(9), pages 936-956, September.
    8. 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.
    9. Wex, Felix & Schryen, Guido & Feuerriegel, Stefan & Neumann, Dirk, 2014. "Emergency response in natural disaster management: Allocation and scheduling of rescue units," European Journal of Operational Research, Elsevier, vol. 235(3), pages 697-708.
    10. Tino Henke & M. Grazia Speranza & Gerhard Wäscher, 2014. "The Multi-Compartment Vehicle Routing Problem with Flexible Compartment Sizes," FEMM Working Papers 140006, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
    11. Yagiura, Mutsunori & Ibaraki, Toshihide, 1996. "The use of dynamic programming in genetic algorithms for permutation problems," European Journal of Operational Research, Elsevier, vol. 92(2), pages 387-401, July.
    12. Pan-Li Zhang & Xiao-Bo Sun & Ji-Quan Wang & Hao-Hao Song & Jin-Ling Bei & Hong-Yu Zhang, 2022. "The Discrete Carnivorous Plant Algorithm with Similarity Elimination Applied to the Traveling Salesman Problem," Mathematics, MDPI, vol. 10(18), pages 1-34, September.
    13. Rafael Martí & Abraham Duarte & Manuel Laguna, 2009. "Advanced Scatter Search for the Max-Cut Problem," INFORMS Journal on Computing, INFORMS, vol. 21(1), pages 26-38, February.
    14. Jonatas B. C. Chagas & Julian Blank & Markus Wagner & Marcone J. F. Souza & Kalyanmoy Deb, 2021. "A non-dominated sorting based customized random-key genetic algorithm for the bi-objective traveling thief problem," Journal of Heuristics, Springer, vol. 27(3), pages 267-301, June.
    15. Jari Kyngäs & Kimmo Nurmi & Nico Kyngäs & George Lilley & Thea Salter & Dries Goossens, 2017. "Scheduling the Australian Football League," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(8), pages 973-982, August.
    16. Rego, César & Duarte, Renato, 2009. "A filter-and-fan approach to the job shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 194(3), pages 650-662, May.
    17. Li, Yanzhi & Tao, Yi & Wang, Fan, 2009. "A compromised large-scale neighborhood search heuristic for capacitated air cargo loading planning," European Journal of Operational Research, Elsevier, vol. 199(2), pages 553-560, December.
    18. Akiyoshi Shioura, 2015. "Polynomial-Time Approximation Schemes for Maximizing Gross Substitutes Utility Under Budget Constraints," Mathematics of Operations Research, INFORMS, vol. 40(1), pages 192-225, February.
    19. Rodriguez-Tello, Eduardo & Hao, Jin-Kao & Torres-Jimenez, Jose, 2008. "An improved simulated annealing algorithm for bandwidth minimization," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1319-1335, March.
    20. Daniels, Richard L. & Rummel, Jeffrey L. & Schantz, Robert, 1998. "A model for warehouse order picking," European Journal of Operational Research, Elsevier, vol. 105(1), pages 1-17, February.

    More about this item

    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:eee:phsmap:v:199:y:1993:i:2:p:232-242. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.