IDEAS home Printed from
   My bibliography  Save this paper

Locating emergency services with priority rules: The priority queuing covering location problem



One of the assumptions of the Capacitated Facility Location Problem (CFLP) is that demand is known and fixed. Most often, this is not the case when managers take some strategic decisions such as locating facilities and assigning demand points to those facilities. In this paper we consider demand as stochastic and we model each of the facilities as an independent queue. Stochastic models of manufacturing systems and deterministic location models are put together in order to obtain a formula for the backlogging probability at a potential facility location. Several solution techniques have been proposed to solve the CFLP. One of the most recently proposed heuristics, a Reactive Greedy Adaptive Search Procedure, is implemented in order to solve the model formulated. We present some computational experiments in order to evaluate the heuristics’ performance and to illustrate the use of this new formulation for the CFLP. The paper finishes with a simple simulation exercise.

Suggested Citation

  • Daniel Serra & Francisco Silva, 2002. "Locating emergency services with priority rules: The priority queuing covering location problem," Economics Working Papers 642, Department of Economics and Business, Universitat Pompeu Fabra, revised May 2008.
  • Handle: RePEc:upf:upfgen:642

    Download full text from publisher

    File URL:
    File Function: Whole Paper
    Download Restriction: no

    References listed on IDEAS

    1. Branas, Charles C. & Revelle, Charles S., 2001. "An iterative switching heuristic to locate hospitals and helicopters," Socio-Economic Planning Sciences, Elsevier, vol. 35(1), pages 11-30, March.
    2. Marianov, Vladimir & Serra, Daniel, 2001. "Hierarchical location-allocation models for congested systems," European Journal of Operational Research, Elsevier, vol. 135(1), pages 195-208, November.
    3. repec:mes:postke:v:13:y:1990:i:2:p:233-235 is not listed on IDEAS
    4. Rajan Batta & Narasimha R. Mannur, 1990. "Covering-Location Models for Emergency Situations That Require Multiple Response Units," Management Science, INFORMS, vol. 36(1), pages 16-23, January.
    5. Vladimir Marianov & Daniel Serra, 1994. "Probabilistic maximal covering location models for congested systems," Economics Working Papers 70, Department of Economics and Business, Universitat Pompeu Fabra.
    6. Michael O. Ball & Feng L. Lin, 1993. "A Reliability Model Applied to Emergency Service Vehicle Location," Operations Research, INFORMS, vol. 41(1), pages 18-36, February.
    7. Oded Berman & Richard C. Larson & Samuel S. Chiu, 1985. "Optimal Server Location on a Network Operating as an M / G /1 Queue," Operations Research, INFORMS, vol. 33(4), pages 746-771, August.
    8. Barton H. Hamilton & Vivian Ho & Dana P. Goldman, 2000. "Queuing for Surgery: Is the U.S. or Canada Worse Off?," The Review of Economics and Statistics, MIT Press, vol. 82(2), pages 297-308, May.
    Full references (including those not matched with items on IDEAS)


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

    Cited by:

    1. repec:iim:iimawp:13011 is not listed on IDEAS
    2. Jayaswal, Sachin, 2014. "Emergency Medical Service System Design under Service Level Constraints for Heterogeneous Patients," IIMA Working Papers WP2014-11-04, Indian Institute of Management Ahmedabad, Research and Publication Department.
    3. Hoseinpour, Pooya & Ahmadi-Javid, Amir, 2016. "A profit-maximization location-capacity model for designing a service system with risk of service interruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 96(C), pages 113-134.

    More about this item


    Location; queuing; greedy heuristics; simulation;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • L80 - Industrial Organization - - Industry Studies: Services - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    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:upf:upfgen:642. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (). General contact details of provider: .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.