IDEAS home Printed from https://ideas.repec.org/a/eee/jomega/v21y1993i4p497-506.html
   My bibliography  Save this article

Alternate solution procedures for the location-routing problem

Author

Listed:
  • Srivastava, R

Abstract

The location-routing problem occurs in the context of physical distribution system design. Important elements in the design of a physical distribution system are location of depots and distribution of goods from depots to customers. Most research on the location of depots assumes that the distribution of goods from depots to customers occurs in a straight to-and-back manner while computing distribution costs, which is true only if the delivery to each customer is a truckload. For less than truckload (LTL) deliveries to customers, multiple customers are served in a single route. Thus, the true distribution costs are the route costs for all customers. The location-routing approach, which considers routing costs during the location of depots overcomes this deficiency. In this research, three new location-routing models are developed and compared. Their overall performance is evaluated in comparison to existing location-routing approaches based on location-allocation modeling, followed by routing on the allocated customer set. The results show the superior performance of the new location-routing models.

Suggested Citation

  • Srivastava, R, 1993. "Alternate solution procedures for the location-routing problem," Omega, Elsevier, vol. 21(4), pages 497-506, July.
    • Handle: RePEc:eee:jomega:v:21:y:1993:i:4:p:497-506
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0305-0483(93)90082-V
    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.

    Citations

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


    Cited by:

    1. Christian Prins & Caroline Prodhon & Angel Ruiz & Patrick Soriano & Roberto Wolfler Calvo, 2007. "Solving the Capacitated Location-Routing Problem by a Cooperative Lagrangean Relaxation-Granular Tabu Search Heuristic," Transportation Science, INFORMS, vol. 41(4), pages 470-483, November.
    2. Ting, Ching-Jung & Chen, Chia-Ho, 2013. "A multiple ant colony optimization algorithm for the capacitated location routing problem," International Journal of Production Economics, Elsevier, vol. 141(1), pages 34-44.
    3. Barreto, Sergio & Ferreira, Carlos & Paixao, Jose & Santos, Beatriz Sousa, 2007. "Using clustering analysis in a capacitated location-routing problem," European Journal of Operational Research, Elsevier, vol. 179(3), pages 968-977, June.
    4. Day, Jamison M. & Daniel Wright, P. & Schoenherr, Tobias & Venkataramanan, Munirpallam & Gaudette, Kevin, 2009. "Improving routing and scheduling decisions at a distributor of industrial gasses," Omega, Elsevier, vol. 37(1), pages 227-237, February.
    5. Karaoglan, Ismail & Altiparmak, Fulya & Kara, Imdat & Dengiz, Berna, 2011. "A branch and cut algorithm for the location-routing problem with simultaneous pickup and delivery," European Journal of Operational Research, Elsevier, vol. 211(2), pages 318-332, June.
    6. Linjie Chen & Thibaud Monteiro & Tao Wang & Eric Marcon, 2019. "Design of shared unit-dose drug distribution network using multi-level particle swarm optimization," Health Care Management Science, Springer, vol. 22(2), pages 304-317, June.
    7. Maucher, Daniel, 2011. "Kommentar zum Design von Logistiknetzwerken," Die Unternehmung - Swiss Journal of Business Research and Practice, Nomos Verlagsgesellschaft mbH & Co. KG, vol. 65(2), pages 151-154.
    8. Mina, Hokey & Jayaraman, Vaidyanathan & Srivastava, Rajesh, 1998. "Combined location-routing problems: A synthesis and future research directions," European Journal of Operational Research, Elsevier, vol. 108(1), pages 1-15, July.
    9. Nagy, Gabor & Salhi, Said, 2007. "Location-routing: Issues, models and methods," European Journal of Operational Research, Elsevier, vol. 177(2), pages 649-672, March.
    10. Gia-Shie Liu & Kuo-Ping Lin, 2020. "The Online Distribution System of Inventory-Routing Problem with Simultaneous Deliveries and Returns Concerning CO 2 Emission Cost," Mathematics, MDPI, vol. 8(6), pages 1-27, June.
    11. Cao, Wenwei & Çelik, Melih & Ergun, Özlem & Swann, Julie & Viljoen, Nadia, 2016. "Challenges in service network expansion: An application in donated breastmilk banking in South Africa," Socio-Economic Planning Sciences, Elsevier, vol. 53(C), pages 33-48.
    12. Karaoglan, Ismail & Altiparmak, Fulya & Kara, Imdat & Dengiz, Berna, 2012. "The location-routing problem with simultaneous pickup and delivery: Formulations and a heuristic approach," Omega, Elsevier, vol. 40(4), pages 465-477.
    13. Roberto Baldacci & Aristide Mingozzi & Roberto Wolfler Calvo, 2011. "An Exact Method for the Capacitated Location-Routing Problem," Operations Research, INFORMS, vol. 59(5), pages 1284-1296, October.
    14. Tuzun, Dilek & Burke, Laura I., 1999. "A two-phase tabu search approach to the location routing problem," European Journal of Operational Research, Elsevier, vol. 116(1), pages 87-99, July.
    15. Caballero, Rafael & Gonzalez, Mercedes & Guerrero, Flor M & Molina, Julian & Paralera, Concepcion, 2007. "Solving a multiobjective location routing problem with a metaheuristic based on tabu search. Application to a real case in Andalusia," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1751-1763, March.
    16. Bagheri Hosseini, Mozhde & Dehghanian, Farzad & Salari, Majid, 2019. "Selective capacitated location-routing problem with incentive-dependent returns in designing used products collection network," European Journal of Operational Research, Elsevier, vol. 272(2), pages 655-673.
    17. Lin, C.K.Y. & Kwok, R.C.W., 2006. "Multi-objective metaheuristics for a location-routing problem with multiple use of vehicles on real data and simulated data," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1833-1849, December.
    18. Hunkar Toyoglu & Oya Ekin Karasan & Bahar Yetis Kara, 2011. "Distribution network design on the battlefield," Naval Research Logistics (NRL), John Wiley & Sons, vol. 58(3), pages 188-209, April.
    19. Nickel, Stefan & Velten, Sebastian, 2017. "Optimization problems with flexible objectives: A general modeling approach and applications," European Journal of Operational Research, Elsevier, vol. 258(1), pages 79-88.
    20. Ambrosino, Daniela & Grazia Scutella, Maria, 2005. "Distribution network design: New problems and related models," European Journal of Operational Research, Elsevier, vol. 165(3), pages 610-624, 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:eee:jomega:v:21:y:1993:i:4:p:497-506. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/375/description#description .

    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.