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Location of Multiple-Server Congestible Facilities for Maximizing Expected Demand, when Services are Non-Essential

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  • Vladimir Marianov

Abstract

We formulate a model for locating multiple-server, congestible facilities. Locations of these facilities maximize total expected demand attended over the region. The effective demand at each node is elastic to the travel time to the facility, and to the congestion at that facility. The facilities to be located are fixed, so customers travel to them in order to receive service or goods, and the demand curves at each demand node (which depend on the travel time and the queue length at the facility), are known. We propose a heuristic for the resulting integer, nonlinear formulation, and provide computational experience. Copyright Kluwer Academic Publishers 2003

Suggested Citation

  • Vladimir Marianov, 2003. "Location of Multiple-Server Congestible Facilities for Maximizing Expected Demand, when Services are Non-Essential," Annals of Operations Research, Springer, vol. 123(1), pages 125-141, October.
    • Handle: RePEc:spr:annopr:v:123:y:2003:i:1:p:125-141:10.1023/a:1026171212594
    DOI: 10.1023/A:1026171212594
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    Citations

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    Cited by:

    1. Jónas Oddur Jónasson & Sarang Deo & Jérémie Gallien, 2017. "Improving HIV Early Infant Diagnosis Supply Chains in Sub-Saharan Africa: Models and Application to Mozambique," Operations Research, INFORMS, vol. 65(6), pages 1479-1493, December.
    2. Boffey, Brian & Galvao, Roberto & Espejo, Luis, 2007. "A review of congestion models in the location of facilities with immobile servers," European Journal of Operational Research, Elsevier, vol. 178(3), pages 643-662, May.
    3. Zaharudin, Zati Aqmar & Brint, Andrew & Genovese, Andrea, 2022. "A multi-period model for reorganising urban household waste recycling networks," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    4. Marianov, Vladimir & Rí­os, Miguel & Icaza, Manuel José, 2008. "Facility location for market capture when users rank facilities by shorter travel and waiting times," European Journal of Operational Research, Elsevier, vol. 191(1), pages 32-44, November.
    5. Simin Huang & Rajan Batta & Rakesh Nagi, 2005. "Distribution network design: Selection and sizing of congested connections," Naval Research Logistics (NRL), John Wiley & Sons, vol. 52(8), pages 701-712, December.
    6. Robert Aboolian & Oded Berman & Vedat Verter, 2016. "Maximal Accessibility Network Design in the Public Sector," Transportation Science, INFORMS, vol. 50(1), pages 336-347, February.
    7. Zhang, Yue & Atkins, Derek, 2019. "Medical facility network design: User-choice and system-optimal models," European Journal of Operational Research, Elsevier, vol. 273(1), pages 305-319.
    8. Sarang Deo & Milind Sohoni, 2015. "Optimal Decentralization of Early Infant Diagnosis of HIV in Resource-Limited Settings," Manufacturing & Service Operations Management, INFORMS, vol. 17(2), pages 191-207, May.
    9. Zhang, Yue & Berman, Oded & Verter, Vedat, 2009. "Incorporating congestion in preventive healthcare facility network design," European Journal of Operational Research, Elsevier, vol. 198(3), pages 922-935, November.
    10. B Boffey & R D Galvão & V Marianov, 2010. "Location of single-server immobile facilities subject to a loss constraint," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(6), pages 987-999, June.
    11. Teodora Dan & Andrea Lodi & Patrice Marcotte, 2020. "Joint location and pricing within a user-optimized environment," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 8(1), pages 61-84, March.
    12. Teodora Dan & Patrice Marcotte, 2019. "Competitive Facility Location with Selfish Users and Queues," Operations Research, INFORMS, vol. 67(2), pages 479-497, March.

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