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Optimizing large-scale emergency medical system operations on highways using the hypercube queuing model

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  • Iannoni, Ana Paula
  • Morabito, Reinaldo
  • Saydam, Cem
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    Abstract

    In this study, we present a series of well-known optimization methods to address two related decisions associated with the design of large-scale ambulance operations on highways: (1) The question of location, and (2) the issue of districting. As a result of computer storage and runtime constraints, previous approaches have only considered small-to-moderate scale problem scenarios, generally employing exact hypercube queuing models integrated into optimization procedures. We overcome these limitations here by embedding a fast and accurate hypercube approximation algorithm adapted for partial backup dispatch policies in single- and multi-start greedy heuristics. The proposed methods are tested on small-to-large-scale problems involving up to 100 ambulances. The results suggest that our approach is a viable alternative for the analysis and configuration of large-scale highway emergency medical systems, providing reasonable accuracy and affordable run times.

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    Bibliographic Info

    Article provided by Elsevier in its journal Socio-Economic Planning Sciences.

    Volume (Year): 45 (2011)
    Issue (Month): 3 (September)
    Pages: 105-117

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    Handle: RePEc:eee:soceps:v:45:y:2011:i:3:p:105-117

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    Web page: http://www.elsevier.com/locate/seps

    Related research

    Keywords: Emergency medical systems Ambulance deployment Approximate hypercube queuing model Multi-start greedy heuristic Probabilistic location and districting problems;

    References

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    1. Iannoni, Ana Paula & Morabito, Reinaldo & Saydam, Cem, 2009. "An optimization approach for ambulance location and the districting of the response segments on highways," European Journal of Operational Research, Elsevier, vol. 195(2), pages 528-542, June.
    2. Morabito, Reinaldo & Chiyoshi, Fernando & Galv√£o, Roberto D., 2008. "Non-homogeneous servers in emergency medical systems: Practical applications using the hypercube queueing model," Socio-Economic Planning Sciences, Elsevier, vol. 42(4), pages 255-270, December.
    3. Armann Ingolfsson & Susan Budge & Erhan Erkut, 2008. "Optimal ambulance location with random delays and travel times," Health Care Management Science, Springer, vol. 11(3), pages 262-274, September.
    4. Kenneth R. Chelst & Ziv Barlach, 1981. "Multiple Unit Dispatches in Emergency Services: Models to Estimate System Performance," Management Science, INFORMS, vol. 27(12), pages 1390-1409, December.
    5. Iannoni, Ana Paula & Morabito, Reinaldo, 2007. "A multiple dispatch and partial backup hypercube queuing model to analyze emergency medical systems on highways," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(6), pages 755-771, November.
    6. Saydam, Cem & Aytug, Haldun, 2003. "Accurate estimation of expected coverage: revisited," Socio-Economic Planning Sciences, Elsevier, vol. 37(1), pages 69-80, March.
    7. J. P. Jarvis, 1985. "Approximating the Equilibrium Behavior of Multi-Server Loss Systems," Management Science, INFORMS, vol. 31(2), pages 235-239, February.
    8. Geroliminis, Nikolas & Karlaftis, Matthew G. & Skabardonis, Alexander, 2009. "A spatial queuing model for the emergency vehicle districting and location problem," Transportation Research Part B: Methodological, Elsevier, vol. 43(7), pages 798-811, August.
    9. Atkinson, J.B. & Kovalenko, I.N. & Kuznetsov, N. & Mykhalevych, K.V., 2008. "A hypercube queueing loss model with customer-dependent service rates," European Journal of Operational Research, Elsevier, vol. 191(1), pages 223-239, November.
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