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The effect of ambulance relocations on the performance of ambulance service providers

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  • van Barneveld, T.C.
  • Bhulai, S.
  • van der Mei, R.D.

Abstract

Dynamic Ambulance Management (DAM) is generally believed to provide means to enhance the response-time performance of emergency medical service providers. The implementation of DAM algorithms leads to additional movements of ambulance vehicles compared to the reactive paradigm, where ambulances depart from the base station when an incident is reported. In practice, proactive relocations are only acceptable when the number of additional movements is limited. Motivated by this trade-off, we study the effect of the number of relocations on the response-time performance. We formulate the relocations from one configuration to a target configuration by the Linear Bottleneck Assignment Problem, so as to provide the quickest way to transition to the target configuration. Moreover, the performance is measured by a general penalty function, assigning to each possible response time a certain penalty. We extensively validate the effectiveness of relocations for a wide variety of realistic scenarios, including a day and night scenario in a critically and realistically loaded system. The results consistently show that already a small number of relocations lead to near-optimal performance, which is important for the implementation of DAM algorithms in practice.

Suggested Citation

  • van Barneveld, T.C. & Bhulai, S. & van der Mei, R.D., 2016. "The effect of ambulance relocations on the performance of ambulance service providers," European Journal of Operational Research, Elsevier, vol. 252(1), pages 257-269.
  • Handle: RePEc:eee:ejores:v:252:y:2016:i:1:p:257-269
    DOI: 10.1016/j.ejor.2015.12.022
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    Cited by:

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    3. Amir Ali Nasrollahzadeh & Amin Khademi & Maria E. Mayorga, 2018. "Real-Time Ambulance Dispatching and Relocation," Manufacturing & Service Operations Management, INFORMS, vol. 20(3), pages 467-480, July.
    4. Akbari, Leilanaz & Kazemi, Ahmad & Salari, Majid, 2023. "Operational planning of vehicles for rescue and relief operations considering the unavailability of the relocated vehicles," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
    5. Khaled Abdelghany & Parya Roustaee & Ahmed Hassan & Aline Karak & Mohammad Khodayar, 2023. "Equilibrium-based Workload Balancing for Robust Emergency Response Operation," Networks and Spatial Economics, Springer, vol. 23(3), pages 715-753, September.
    6. Bélanger, V. & Ruiz, A. & Soriano, P., 2019. "Recent optimization models and trends in location, relocation, and dispatching of emergency medical vehicles," European Journal of Operational Research, Elsevier, vol. 272(1), pages 1-23.
    7. Enayati, Shakiba & Mayorga, Maria E. & Rajagopalan, Hari K. & Saydam, Cem, 2018. "Real-time ambulance redeployment approach to improve service coverage with fair and restricted workload for EMS providers," Omega, Elsevier, vol. 79(C), pages 67-80.
    8. Martin van Buuren & Caroline Jagtenberg & Thije van Barneveld & Rob van der Mei & Sandjai Bhulai, 2018. "Ambulance Dispatch Center Pilots Proactive Relocation Policies to Enhance Effectiveness," Interfaces, INFORMS, vol. 48(3), pages 235-246, June.
    9. Drent, Collin & Keizer, Minou Olde & Houtum, Geert-Jan van, 2020. "Dynamic dispatching and repositioning policies for fast-response service networks," European Journal of Operational Research, Elsevier, vol. 285(2), pages 583-598.
    10. Liu, Yang & Cui, Na & Zhang, Jianghua, 2019. "Integrated temporary facility location and casualty allocation planning for post-disaster humanitarian medical service," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 1-16.
    11. Carvalho, A.S. & Captivo, M.E. & Marques, I., 2020. "Integrating the ambulance dispatching and relocation problems to maximize system’s preparedness," European Journal of Operational Research, Elsevier, vol. 283(3), pages 1064-1080.

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