IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v86y1999i0p529-55810.1023-a1018939709890.html
   My bibliography  Save this article

New classes of efficiently solvable generalized Traveling Salesman Problems

Author

Listed:
  • E. Balas

Abstract

We consider the n‐city traveling salesman problem (TSP), symmetric or asymmetric,with the following attributes. In one case, a positive integer k and an ordering (1,..., n) ofthe cities is given, and an optimal tour is sought subject to the condition that for any pairi, j ∈ (1..., n), if j ≥ i + k, then i precedes j in the tour. In another case, position i in the tourhas to be assigned to some city within k positions from i in the above ordering. This case isclosely related to the TSP with time windows. In a third case, an optimal tour visiting m outof n cities is sought subject to constraints of the above two types. This is a special case ofthe Prize Collecting TSP (PCTSP). In any of the three cases, k may be replaced by city‐specificintegers k(i), i=1,..., n. These problems arise in practice. For each class, we reducethe problem to that of finding a shortest source‐sink path in a layered network with a numberof arcs linear in n and exponential in the parameter k (which is independent of the problemsize). Besides providing linear time algorithms for the solution of these problems, the reductionto a shortest path problem also provides a compact linear programming formulation.Finally, for TSPs or PCTSPs that do not have the required attributes, these algorithms canbe used as heuristics that find in linear time a local optimum over an exponential‐sizeneighborhood. Copyright Kluwer Academic Publishers 1999

Suggested Citation

  • E. Balas, 1999. "New classes of efficiently solvable generalized Traveling Salesman Problems," Annals of Operations Research, Springer, vol. 86(0), pages 529-558, January.
  • Handle: RePEc:spr:annopr:v:86:y:1999:i:0:p:529-558:10.1023/a:1018939709890
    DOI: 10.1023/A:1018939709890
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1023/A:1018939709890
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1023/A:1018939709890?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Eranda Çela & Vladimir G. Deineko & Gerhard J. Woeginger, 2017. "The multi-stripe travelling salesman problem," Annals of Operations Research, Springer, vol. 259(1), pages 21-34, December.
    2. Nicola Secomandi & François Margot, 2009. "Reoptimization Approaches for the Vehicle-Routing Problem with Stochastic Demands," Operations Research, INFORMS, vol. 57(1), pages 214-230, February.
    3. Vu, Duc Minh & Hewitt, Mike & Vu, Duc D., 2022. "Solving the time dependent minimum tour duration and delivery man problems with dynamic discretization discovery," European Journal of Operational Research, Elsevier, vol. 302(3), pages 831-846.
    4. Dominique Feillet & Pierre Dejax & Michel Gendreau, 2005. "Traveling Salesman Problems with Profits," Transportation Science, INFORMS, vol. 39(2), pages 188-205, May.
    5. Jayanth Krishna Mogali & Joris Kinable & Stephen F. Smith & Zachary B. Rubinstein, 2021. "Scheduling for multi-robot routing with blocking and enabling constraints," Journal of Scheduling, Springer, vol. 24(3), pages 291-318, June.
    6. de Weerdt, Mathijs & Baart, Robert & He, Lei, 2021. "Single-machine scheduling with release times, deadlines, setup times, and rejection," European Journal of Operational Research, Elsevier, vol. 291(2), pages 629-639.
    7. Timo Hintsch & Stefan Irnich, 2017. "Large Multiple Neighborhood Search for the Clustered Vehicle-Routing Problem," Working Papers 1701, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    8. Christian Tilk & Stefan Irnich, 2014. "Dynamic Programming for the Minimum Tour Duration Problem," Working Papers 1408, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz, revised 04 Aug 2014.
    9. Oleg L. Tashlykov & Alexander N. Sesekin & Alexander G. Chentsov & Alexei A. Chentsov, 2022. "Development of Methods for Route Optimization of Work in Inhomogeneous Radiation Fields to Minimize the Dose Load of Personnel," Energies, MDPI, vol. 15(13), pages 1-11, June.
    10. Timo Hintsch, 2019. "Large Multiple Neighborhood Search for the Soft-Clustered Vehicle-Routing Problem," Working Papers 1904, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    11. 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.
    12. Richard K. Congram & Chris N. Potts & Steef L. van de Velde, 2002. "An Iterated Dynasearch Algorithm for the Single-Machine Total Weighted Tardiness Scheduling Problem," INFORMS Journal on Computing, INFORMS, vol. 14(1), pages 52-67, February.
    13. Hintsch, Timo & Irnich, Stefan, 2018. "Large multiple neighborhood search for the clustered vehicle-routing problem," European Journal of Operational Research, Elsevier, vol. 270(1), pages 118-131.
    14. Andre A. Cire & Willem-Jan van Hoeve, 2013. "Multivalued Decision Diagrams for Sequencing Problems," Operations Research, INFORMS, vol. 61(6), pages 1411-1428, December.
    15. Egon Balas & Neil Simonetti, 2001. "Linear Time Dynamic-Programming Algorithms for New Classes of Restricted TSPs: A Computational Study," INFORMS Journal on Computing, INFORMS, vol. 13(1), pages 56-75, February.
    16. Christian Tilk & Stefan Irnich, 2017. "Dynamic Programming for the Minimum Tour Duration Problem," Transportation Science, INFORMS, vol. 51(2), pages 549-565, May.

    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:spr:annopr:v:86:y:1999:i:0:p:529-558:10.1023/a:1018939709890. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.