IDEAS home Printed from https://ideas.repec.org/a/pal/jorsoc/v62y2011i1d10.1057_jors.2009.176.html
   My bibliography  Save this article

A robust enhancement to the Clarke–Wright savings algorithm

Author

Listed:
  • T Doyuran

    (Sabanci University)

  • B Çatay

    (Sabanci University)

Abstract

We address the Clarke and Wright (CW) savings algorithm proposed for the Capacitated Vehicle Routing Problem. We first consider a recent enhancement that uses the put first larger items idea originally proposed for the bin packing problem and show that the conflicting idea of putting smaller items first has a comparable performance. Next, we propose a robust enhancement to the CW savings formulation. The proposed formulation is normalized to efficiently solve different problems, independent from the measurement units and parameter intervals. To test the performance of the proposed savings function, we conduct an extensive computational study on a large set of well-known instances from the literature. Our results show that the proposed savings function provides shorter distances in the majority of the instances and the average performance is significantly better than previously presented enhancements.

Suggested Citation

  • 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.
    • Handle: RePEc:pal:jorsoc:v:62:y:2011:i:1:d:10.1057_jors.2009.176
    DOI: 10.1057/jors.2009.176
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/jors.2009.176
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/jors.2009.176?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. B. Dantzig & J. H. Ramser, 1959. "The Truck Dispatching Problem," Management Science, INFORMS, vol. 6(1), pages 80-91, October.
    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.
    3. 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.
    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. Gilbert Laporte, 2009. "Fifty Years of Vehicle Routing," Transportation Science, INFORMS, vol. 43(4), pages 408-416, November.
    2. 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.
    3. 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).
    4. 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.
    5. Jumbo, Olga & Moghaddass, Ramin, 2022. "Resource optimization and image processing for vegetation management programs in power distribution networks," Applied Energy, Elsevier, vol. 319(C).
    6. Qi, Mingyao & Lin, Wei-Hua & Li, Nan & Miao, Lixin, 2012. "A spatiotemporal partitioning approach for large-scale vehicle routing problems with time windows," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 248-257.
    7. Srinivas, Sharan & Ramachandiran, Surya & Rajendran, Suchithra, 2022. "Autonomous robot-driven deliveries: A review of recent developments and future directions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 165(C).
    8. Müller, Juliane, 2010. "Approximative solutions to the bicriterion Vehicle Routing Problem with Time Windows," European Journal of Operational Research, Elsevier, vol. 202(1), pages 223-231, April.
    9. Martinhon, Carlos & Lucena, Abilio & Maculan, Nelson, 2004. "Stronger K-tree relaxations for the vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 158(1), pages 56-71, October.
    10. 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.
    11. Majsa Ammouriova & Massimo Bertolini & Juliana Castaneda & Angel A. Juan & Mattia Neroni, 2022. "A Heuristic-Based Simulation for an Education Process to Learn about Optimization Applications in Logistics and Transportation," Mathematics, MDPI, vol. 10(5), pages 1-18, March.
    12. 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.
    13. Jorge Oyola & Halvard Arntzen & David L. Woodruff, 2017. "The stochastic vehicle routing problem, a literature review, Part II: solution methods," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 6(4), pages 349-388, December.
    14. Diego Cattaruzza & Nabil Absi & Dominique Feillet, 2018. "Vehicle routing problems with multiple trips," Annals of Operations Research, Springer, vol. 271(1), pages 127-159, December.
    15. Diego Cattaruzza & Nabil Absi & Dominique Feillet, 2016. "Vehicle routing problems with multiple trips," 4OR, Springer, vol. 14(3), pages 223-259, September.
    16. 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.
    17. Briseida Sarasola & Karl Doerner & Verena Schmid & Enrique Alba, 2016. "Variable neighborhood search for the stochastic and dynamic vehicle routing problem," Annals of Operations Research, Springer, vol. 236(2), pages 425-461, January.
    18. Vidal, Thibaut & Crainic, Teodor Gabriel & Gendreau, Michel & Prins, Christian, 2013. "Heuristics for multi-attribute vehicle routing problems: A survey and synthesis," European Journal of Operational Research, Elsevier, vol. 231(1), pages 1-21.
    19. Gerald Senarclens de Grancy & Marc Reimann, 2016. "Vehicle routing problems with time windows and multiple service workers: a systematic comparison between ACO and GRASP," 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. 24(1), pages 29-48, March.
    20. Karina Thiebaut & Artur Pessoa, 2023. "Approximating the chance-constrained capacitated vehicle routing problem with robust optimization," 4OR, Springer, vol. 21(3), pages 513-531, September.

    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:62:y:2011:i:1:d:10.1057_jors.2009.176. 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.