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Strategic ambulance location for heterogeneous regions

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  • Leknes, Håkon
  • Aartun, Eirik Skorge
  • Andersson, Henrik
  • Christiansen, Marielle
  • Granberg, Tobias Andersson

Abstract

Providing Emergency Medical Services (EMS) is a key function of society. To achieve high quality EMS, planning is of vital importance. An important strategic and tactical problem is the location of ambulance stations and the allocation of ambulances to these stations. This paper presents a new mixed integer model for this problem especially suitable for regions with heterogeneous demand and multiple performance measures. The model decides on the location/allocation of stations/ambulances, calculates the service and arrival rates for each station and the probabilities that a call is served by a particular station. The model is tested on a combined urban and rural area in Norway with multiple performance measures. Compared with the current solution for the area, the best solution from the model has a higher expected performance on each of the performance measures used.

Suggested Citation

  • Leknes, Håkon & Aartun, Eirik Skorge & Andersson, Henrik & Christiansen, Marielle & Granberg, Tobias Andersson, 2017. "Strategic ambulance location for heterogeneous regions," European Journal of Operational Research, Elsevier, vol. 260(1), pages 122-133.
    • Handle: RePEc:eee:ejores:v:260:y:2017:i:1:p:122-133
    DOI: 10.1016/j.ejor.2016.12.020
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    Cited by:

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    4. Caio Vitor Beojone & Regiane Máximo de Souza & Ana Paula Iannoni, 2021. "An Efficient Exact Hypercube Model with Fully Dedicated Servers," Transportation Science, INFORMS, vol. 55(1), pages 222-237, 1-2.
    5. Jian Wang & Yin Wang & Mingzhu Yu, 0. "A multi-period ambulance location and allocation problem in the disaster," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-24.
    6. Sheikholeslami, Mahnaz & Zarrinpoor, Naeme, 2023. "Designing an integrated humanitarian logistics network for the preparedness and response phases under uncertainty," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    7. Shaoren Wang & Yenchun Jim Wu & Ruiting Li, 2022. "An Improved Genetic Algorithm for Location Allocation Problem with Grey Theory in Public Health Emergencies," IJERPH, MDPI, vol. 19(15), pages 1-18, August.
    8. Wajid, Shayesta & Nezamuddin, N., 2023. "Capturing delays in response of emergency services in Delhi," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
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    10. Heewon Chea & Hyun Kim & Shih-Lung Shaw & Yongwan Chun, 2022. "Assessing Trauma Center Accessibility for Healthcare Equity Using an Anti-Covering Approach," IJERPH, MDPI, vol. 19(3), pages 1-21, January.

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