IDEAS home Printed from https://ideas.repec.org/a/inm/oropre/v31y1983i2p292-303.html
   My bibliography  Save this article

Optimal Locations for a Class of Nonlinear, Single-Facility Location Problems on a Network

Author

Listed:
  • D. R. Shier

    (Clemson University, Clemson, South Carolina)

  • P. M. Dearing

    (Clemson University, Clemson, South Carolina)

Abstract

This paper investigates a class of single-facility location problems on an arbitrary network. Necessary and sufficient conditions are obtained for characterizing locally optimal locations with respect to a certain nonlinear objective function. This approach produces a number of new results for locating a facility on an arbitrary network, and in addition it unifies several known results for the special case of tree networks. It also suggests algorithmic procedures for obtaining such optimal locations.

Suggested Citation

  • D. R. Shier & P. M. Dearing, 1983. "Optimal Locations for a Class of Nonlinear, Single-Facility Location Problems on a Network," Operations Research, INFORMS, vol. 31(2), pages 292-303, April.
    • Handle: RePEc:inm:oropre:v:31:y:1983:i:2:p:292-303
    DOI: 10.1287/opre.31.2.292
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/opre.31.2.292
    Download Restriction: no
    File URL: https://libkey.io/10.1287/opre.31.2.292?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
    ---><---

    Citations

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


    Cited by:

    1. Jianfeng Lu & Qiang Yang, 2022. "Location Optimization of Emergency Station for Dangerous Goods Accidents Considering Risk," Sustainability, MDPI, vol. 14(10), pages 1-11, May.
    2. R. Francis & T. Lowe & M. Rayco & A. Tamir, 2009. "Aggregation error for location models: survey and analysis," Annals of Operations Research, Springer, vol. 167(1), pages 171-208, March.
    3. R. L. Francis & T. J. Lowe & Arie Tamir, 2000. "Aggregation Error Bounds for a Class of Location Models," Operations Research, INFORMS, vol. 48(2), pages 294-307, April.
    4. Rafael Blanquero & Emilio Carrizosa & Amaya Nogales-Gómez & Frank Plastria, 2014. "Single-facility huff location problems on networks," Annals of Operations Research, Springer, vol. 222(1), pages 175-195, November.
    5. Zhi-Chun Li & Qian Liu, 2020. "Optimal deployment of emergency rescue stations in an urban transportation corridor," Transportation, Springer, vol. 47(1), pages 445-473, February.

    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:inm:oropre:v:31:y:1983:i:2:p:292-303. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.