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


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


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

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    References listed on IDEAS

    1. 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.
    2. 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.
    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. 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.
    5. J. P. Jarvis, 1985. "Approximating the Equilibrium Behavior of Multi-Server Loss Systems," Management Science, INFORMS, vol. 31(2), pages 235-239, February.
    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. 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.
    8. 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.
    9. 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.
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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. de Souza, Regiane Máximo & Morabito, Reinaldo & Chiyoshi, Fernando Y. & Iannoni, Ana Paula, 2015. "Incorporating priorities for waiting customers in the hypercube queuing model with application to an emergency medical service system in Brazil," European Journal of Operational Research, Elsevier, vol. 242(1), pages 274-285.


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