IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v208y2011i3p221-232.html
   My bibliography  Save this article

Lin-Kernighan heuristic adaptations for the generalized traveling salesman problem

Author

Listed:
  • Karapetyan, D.
  • Gutin, G.

Abstract

The Lin-Kernighan heuristic is known to be one of the most successful heuristics for the Traveling Salesman Problem (TSP). It has also proven its efficiency in application to some other problems. In this paper, we discuss possible adaptations of TSP heuristics for the generalized traveling salesman problem (GTSP) and focus on the case of the Lin-Kernighan algorithm. At first, we provide an easy-to-understand description of the original Lin-Kernighan heuristic. Then we propose several adaptations, both trivial and complicated. Finally, we conduct a fair competition between all the variations of the Lin-Kernighan adaptation and some other GTSP heuristics. It appears that our adaptation of the Lin-Kernighan algorithm for the GTSP reproduces the success of the original heuristic. Different variations of our adaptation outperform all other heuristics in a wide range of trade-offs between solution quality and running time, making Lin-Kernighan the state-of-the-art GTSP local search.

Suggested Citation

  • Karapetyan, D. & Gutin, G., 2011. "Lin-Kernighan heuristic adaptations for the generalized traveling salesman problem," European Journal of Operational Research, Elsevier, vol. 208(3), pages 221-232, February.
  • Handle: RePEc:eee:ejores:v:208:y:2011:i:3:p:221-232
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(10)00548-5
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Egon Balas & Matthew J. Saltzman, 1991. "An Algorithm for the Three-Index Assignment Problem," Operations Research, INFORMS, vol. 39(1), pages 150-161, February.
    2. Renaud, Jacques & Boctor, Fayez F., 1998. "An efficient composite heuristic for the symmetric generalized traveling salesman problem," European Journal of Operational Research, Elsevier, vol. 108(3), pages 571-584, August.
    3. 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.
    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.
    5. Charles E. Noon & James C. Bean, 1991. "A Lagrangian Based Approach for the Asymmetric Generalized Traveling Salesman Problem," Operations Research, INFORMS, vol. 39(4), pages 623-632, August.
    6. Pop, Petrica C. & Kern, W. & Still, G., 2006. "A new relaxation method for the generalized minimum spanning tree problem," European Journal of Operational Research, Elsevier, vol. 170(3), pages 900-908, May.
    7. Matteo Fischetti & Juan José Salazar González & Paolo Toth, 1997. "A Branch-and-Cut Algorithm for the Symmetric Generalized Traveling Salesman Problem," Operations Research, INFORMS, vol. 45(3), pages 378-394, June.
    8. Snyder, Lawrence V. & Daskin, Mark S., 2006. "A random-key genetic algorithm for the generalized traveling salesman problem," European Journal of Operational Research, Elsevier, vol. 174(1), pages 38-53, October.
    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. Markus Leitner, 2016. "Integer programming models and branch-and-cut approaches to generalized {0,1,2}-survivable network design problems," Computational Optimization and Applications, Springer, vol. 65(1), pages 73-92, September.
    2. Pop, Petrică C. & Cosma, Ovidiu & Sabo, Cosmin & Sitar, Corina Pop, 2024. "A comprehensive survey on the generalized traveling salesman problem," European Journal of Operational Research, Elsevier, vol. 314(3), pages 819-835.
    3. 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.
    4. Gary R. Waissi & Pragya Kaushal, 2020. "A polynomial matrix processing heuristic algorithm for finding high quality feasible solutions for the TSP," OPSEARCH, Springer;Operational Research Society of India, vol. 57(1), pages 73-87, March.
    5. Gahm, Christian & Brabänder, Christian & Tuma, Axel, 2017. "Vehicle routing with private fleet, multiple common carriers offering volume discounts, and rental options," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 97(C), pages 192-216.
    6. Gustavo Erick Anaya Fuentes & Eva Selene Hernández Gress & Juan Carlos Seck Tuoh Mora & Joselito Medina Marín, 2018. "Solution to travelling salesman problem by clusters and a modified multi-restart iterated local search metaheuristic," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-20, August.
    7. Baniasadi, Pouya & Foumani, Mehdi & Smith-Miles, Kate & Ejov, Vladimir, 2020. "A transformation technique for the clustered generalized traveling salesman problem with applications to logistics," European Journal of Operational Research, Elsevier, vol. 285(2), pages 444-457.

    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. 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.
    2. Karapetyan, D. & Gutin, G., 2012. "Efficient local search algorithms for known and new neighborhoods for the generalized traveling salesman problem," European Journal of Operational Research, Elsevier, vol. 219(2), pages 234-251.
    3. Bruce Golden & Zahra Naji-Azimi & S. Raghavan & Majid Salari & Paolo Toth, 2012. "The Generalized Covering Salesman Problem," INFORMS Journal on Computing, INFORMS, vol. 24(4), pages 534-553, November.
    4. Pop, Petrică C. & Cosma, Ovidiu & Sabo, Cosmin & Sitar, Corina Pop, 2024. "A comprehensive survey on the generalized traveling salesman problem," European Journal of Operational Research, Elsevier, vol. 314(3), pages 819-835.
    5. Gharehgozli, Amir & Yu, Yugang & de Koster, René & Du, Shaofu, 2019. "Sequencing storage and retrieval requests in a container block with multiple open locations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 261-284.
    6. Rajabighamchi, Farzaneh & van Hoesel, Stan & Defryn, Christof, 2023. "The order picking problem under a scattered storage policy," Research Memorandum 006, Maastricht University, Graduate School of Business and Economics (GSBE).
    7. Amir Hossein Gharehgozli & Gilbert Laporte & Yugang Yu & René de Koster, 2015. "Scheduling Twin Yard Cranes in a Container Block," Transportation Science, INFORMS, vol. 49(3), pages 686-705, August.
    8. Dontas, Michael & Sideris, Georgios & Manousakis, Eleftherios G. & Zachariadis, Emmanouil E., 2023. "An adaptive memory matheuristic for the set orienteering problem," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1010-1023.
    9. Mehdi El Krari & Belaïd Ahiod & Youssef Bouazza El Benani, 2021. "A pre-processing reduction method for the generalized travelling salesman problem," Operational Research, Springer, vol. 21(4), pages 2543-2591, December.
    10. W Zahrouni & H Kamoun, 2011. "Transforming part-sequencing problems in a robotic cell into a GTSP," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(1), pages 114-123, January.
    11. Kang, Seungmo & Ouyang, Yanfeng, 2011. "The traveling purchaser problem with stochastic prices: Exact and approximate algorithms," European Journal of Operational Research, Elsevier, vol. 209(3), pages 265-272, March.
    12. Snyder, Lawrence V. & Daskin, Mark S., 2006. "A random-key genetic algorithm for the generalized traveling salesman problem," European Journal of Operational Research, Elsevier, vol. 174(1), pages 38-53, October.
    13. Feremans, Corinne & Labbe, Martine & Laporte, Gilbert, 2003. "Generalized network design problems," European Journal of Operational Research, Elsevier, vol. 148(1), pages 1-13, July.
    14. Baniasadi, Pouya & Foumani, Mehdi & Smith-Miles, Kate & Ejov, Vladimir, 2020. "A transformation technique for the clustered generalized traveling salesman problem with applications to logistics," European Journal of Operational Research, Elsevier, vol. 285(2), pages 444-457.
    15. Gharehgozli, Amir & Zaerpour, Nima, 2020. "Robot scheduling for pod retrieval in a robotic mobile fulfillment system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    16. F. Carrabs & R. Cerulli & R. Pentangelo & A. Raiconi, 2018. "A two-level metaheuristic for the all colors shortest path problem," Computational Optimization and Applications, Springer, vol. 71(2), pages 525-551, November.
    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. Pop, Petrică C., 2020. "The generalized minimum spanning tree problem: An overview of formulations, solution procedures and latest advances," European Journal of Operational Research, Elsevier, vol. 283(1), pages 1-15.
    19. 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.
    20. Jiang, Zhongzhou & Liu, Jing & Wang, Shuai, 2016. "Traveling salesman problems with PageRank Distance on complex networks reveal community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 293-302.

    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:ejores:v:208:y:2011:i:3:p:221-232. 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.elsevier.com/locate/eor .

    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.