IDEAS home Printed from https://ideas.repec.org/a/pal/jorsoc/v61y2010i8d10.1057_jors.2009.89.html
   My bibliography  Save this article

Fine-tuning a parametric Clarke and Wright heuristic by means of EAGH (empirically adjusted greedy heuristics)

Author

Listed:
  • A Corominas

    (Institute of Industrial and Control Engineering, Universitat Politècnica de Catalunya (UPC))

  • A García-Villoria

    (Institute of Industrial and Control Engineering, Universitat Politècnica de Catalunya (UPC))

  • R Pastor

    (Institute of Industrial and Control Engineering, Universitat Politècnica de Catalunya (UPC))

Abstract

Altınel and Öncan (2005) (A new enhancement of the Clarke and Wright savings heuristic for the capacitated vehicle routing problem) proposed a parametric Clarke and Wright heuristic to solve the capacitated vehicle routing problem (CVRP). The performance of this parametric heuristic is sensitive to fine-tuning. Antinel and Öncan used an enumerative parameter-setting approach and improved on the results obtained with the original Clarke and Wright heuristic, but their approach requires much more computation time to solve an instance. Battarra et al (2008) (Tuning a parametric Clarke–Wright heuristic through a genetic algorithm) proposed a genetic algorithm to set the parameter values. They succeeded in reducing the time needed to solve an instance, but the quality of the solution was slightly worse. In this paper, we propose to use the EAGH (empirically adjusted greedy heuristics) procedure to set the parameter values. A computational experiment shows the efficiency of EAGH; in an even shorter time, we improve on the best results obtained with any parametric Clarke and Wright heuristic method proposed in the literature.

Suggested Citation

  • A Corominas & A García-Villoria & R Pastor, 2010. "Fine-tuning a parametric Clarke and Wright heuristic by means of EAGH (empirically adjusted greedy heuristics)," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(8), pages 1309-1314, August.
  • Handle: RePEc:pal:jorsoc:v:61:y:2010:i:8:d:10.1057_jors.2009.89
    DOI: 10.1057/jors.2009.89
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/jors.2009.89
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1057/jors.2009.89?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. G. Clarke & J. W. Wright, 1964. "Scheduling of Vehicles from a Central Depot to a Number of Delivery Points," Operations Research, INFORMS, vol. 12(4), pages 568-581, August.
    2. Paessens, H., 1988. "The savings algorithm for the vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 34(3), pages 336-344, March.
    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. Yuan Zhang & Yu Yuan & Kejing Lu, 2020. "RETRACTED ARTICLE: E-commerce information system data analytics by advanced ACO for asymmetric capacitated vehicle delivery routing," Information Systems and e-Business Management, Springer, vol. 18(4), pages 911-929, December.

    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. Haughton, Michael A., 1998. "The performance of route modification and demand stabilization strategies in stochastic vehicle routing," Transportation Research Part B: Methodological, Elsevier, vol. 32(8), pages 551-566, November.
    2. Loske, Dominic & Klumpp, Matthias, 2021. "Human-AI collaboration in route planning: An empirical efficiency-based analysis in retail logistics," International Journal of Production Economics, Elsevier, vol. 241(C).
    3. Javier Faulin & Pablo Sarobe & Jorge Simal, 2005. "The DSS LOGDIS Optimizes Delivery Routes for FRILAC’s Frozen Products," Interfaces, INFORMS, vol. 35(3), pages 202-214, June.
    4. A A Juan & J Faulin & J Jorba & D Riera & D Masip & B Barrios, 2011. "On the use of Monte Carlo simulation, cache and splitting techniques to improve the Clarke and Wright savings heuristics," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(6), pages 1085-1097, June.
    5. M. Kritikos & G. Ioannou, 2017. "A greedy heuristic for the capacitated minimum spanning tree problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(10), pages 1223-1235, October.
    6. Park, Junhyuk & Kim, Byung-In, 2010. "The school bus routing problem: A review," European Journal of Operational Research, Elsevier, vol. 202(2), pages 311-319, April.
    7. Gilbert Laporte, 2009. "Fifty Years of Vehicle Routing," Transportation Science, INFORMS, vol. 43(4), pages 408-416, November.
    8. Wadi Khalid Anuar & Lai Soon Lee & Hsin-Vonn Seow & Stefan Pickl, 2022. "A Multi-Depot Dynamic Vehicle Routing Problem with Stochastic Road Capacity: An MDP Model and Dynamic Policy for Post-Decision State Rollout Algorithm in Reinforcement Learning," Mathematics, MDPI, vol. 10(15), pages 1-70, July.
    9. Zachariadis, Emmanouil E. & Tarantilis, Christos D. & Kiranoudis, Chris T., 2010. "An adaptive memory methodology for the vehicle routing problem with simultaneous pick-ups and deliveries," European Journal of Operational Research, Elsevier, vol. 202(2), pages 401-411, April.
    10. Van Breedam, Alex, 2002. "A parametric analysis of heuristics for the vehicle routing problem with side-constraints," European Journal of Operational Research, Elsevier, vol. 137(2), pages 348-370, March.
    11. Vigo, Daniele, 1996. "A heuristic algorithm for the asymmetric capacitated vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 89(1), pages 108-126, February.
    12. C D Tarantilis & C T Kiranoudis & V S Vassiliadis, 2003. "A list based threshold accepting metaheuristic for the heterogeneous fixed fleet vehicle routing problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(1), pages 65-71, January.
    13. Tarantilis, C.D. & Kiranoudis, C.T., 2007. "A flexible adaptive memory-based algorithm for real-life transportation operations: Two case studies from dairy and construction sector," European Journal of Operational Research, Elsevier, vol. 179(3), pages 806-822, June.
    14. Rieck, Julia, 2011. "Ein Framework fu?r die Gestaltung grosser, internationaler Transportnetze: Beru?cksichtigung von Netzwerkdesign und Tourenbildung," Die Unternehmung - Swiss Journal of Business Research and Practice, Nomos Verlagsgesellschaft mbH & Co. KG, vol. 65(2), pages 133-150.
    15. T Doyuran & B Çatay, 2011. "A robust enhancement to the Clarke–Wright savings algorithm," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(1), pages 223-231, January.
    16. M Battarra & B Golden & D Vigo, 2008. "Tuning a parametric Clarke–Wright heuristic via a genetic algorithm," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(11), pages 1568-1572, November.
    17. T Öncan & İ K Altınel, 2009. "Parametric enhancements of the Esau–Williams heuristic for the capacitated minimum spanning tree problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(2), pages 259-267, February.
    18. Tarantilis, C. D. & Kiranoudis, C. T. & Vassiliadis, V. S., 2004. "A threshold accepting metaheuristic for the heterogeneous fixed fleet vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 152(1), pages 148-158, January.
    19. Chiang, Wen-Chyuan & Russell, Robert A., 2004. "Integrating purchasing and routing in a propane gas supply chain," European Journal of Operational Research, Elsevier, vol. 154(3), pages 710-729, May.
    20. Martin Schwardt & Kathrin Fischer, 2009. "Combined location-routing problems—a neural network approach," Annals of Operations Research, Springer, vol. 167(1), pages 253-269, March.

    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:61:y:2010:i:8:d:10.1057_jors.2009.89. 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.