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Non-homogeneous servers in emergency medical systems: Practical applications using the hypercube queueing model


  • Morabito, Reinaldo
  • Chiyoshi, Fernando
  • Galvão, Roberto D.


In this paper, we study the effects of considering homogeneous versus non-homogeneous servers in applications of the hypercube queueing model. This is important since approximate methods available for solving the model for homogeneous servers are computationally much less time-consuming than the exact methods required for the non-homogeneous case. Illustrative examples are initially presented to show the degree to which using homogeneous versus non-homogeneous servers can differ. Then, two ambulance deployment applications dealing with Brazilian emergency medical systems, in a city and along a highway, are analyzed. The basic operational characteristics of non-homogeneous systems were compared to the respective predictions produced under the simplifying assumption of homogeneous servers. It was found that, even when the degree of non-homogeneity of the servers is not highly significant, homogeneity may lead to poor predictions of the actual operational characteristics of non-homogeneous systems.

Suggested Citation

  • Morabito, Reinaldo & Chiyoshi, Fernando & Galvão, 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.
  • Handle: RePEc:eee:soceps:v:42:y:2008:i:4:p:255-270

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    References listed on IDEAS

    1. J. P. Jarvis, 1985. "Approximating the Equilibrium Behavior of Multi-Server Loss Systems," Management Science, INFORMS, vol. 31(2), pages 235-239, February.
    2. Brotcorne, Luce & Laporte, Gilbert & Semet, Frederic, 2003. "Ambulance location and relocation models," European Journal of Operational Research, Elsevier, vol. 147(3), pages 451-463, June.
    3. Saydam, Cem & Aytug, Haldun, 2003. "Accurate estimation of expected coverage: revisited," Socio-Economic Planning Sciences, Elsevier, vol. 37(1), pages 69-80, March.
    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.
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    Cited by:

    1. Boyacı, Burak & Geroliminis, Nikolas, 2015. "Approximation methods for large-scale spatial queueing systems," Transportation Research Part B: Methodological, Elsevier, vol. 74(C), pages 151-181.
    2. Iannoni, Ana Paula & Morabito, Reinaldo & Saydam, Cem, 2011. "Optimizing large-scale emergency medical system operations on highways using the hypercube queuing model," Socio-Economic Planning Sciences, Elsevier, vol. 45(3), pages 105-117, September.
    3. L. C. Nogueira & L. R. Pinto & P. M. S. Silva, 2016. "Reducing Emergency Medical Service response time via the reallocation of ambulance bases," Health Care Management Science, Springer, vol. 19(1), pages 31-42, March.
    4. Geroliminis, Nikolas & Kepaptsoglou, Konstantinos & Karlaftis, Matthew G., 2011. "A hybrid hypercube - Genetic algorithm approach for deploying many emergency response mobile units in an urban network," European Journal of Operational Research, Elsevier, vol. 210(2), pages 287-300, April.


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