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Optimization for the Locations of Ambulances under Two-Stage Life Rescue in the Emergency Medical Service: A Case Study in Shanghai, China

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  • Ming Liu
  • Dapeng Yang
  • Fengxia Hao

Abstract

With the development of society, public resources for healthcare are increasingly inadequate to meet the demands for the services. Therefore, it is extremely important for policymakers to provide citizens with the most effective healthcare services within the limited available resources. In order to achieve positive effect rescue operations in the Emergency Medical Services (EMS) system, the problems including where to locate the ambulance facilities and how many ambulance vehicles should be allocated to the stations have become the focus of attention. In this paper, we study the problem based on the demand for EMS in Songjiang District, Shanghai, China, followed by the joint planning of Emergency Medical Services management, which typically consists of ambulance facility locations planning and patient’s assignment to hospitals. We proposed a modified Double Standard Model (DSM) to maximize the demand points covered at least two times within the minimum coverage criteria. The problem is solved by integer linear programming technique with the CPLEX software and we make a comparison between the solutions and the locations which exist in the emergency system used by the Songjiang emergency center. Our results show that the demand coverage rate and response time can be efficiently improved through relocating the current facilities without additional vehicle resources.

Suggested Citation

  • Ming Liu & Dapeng Yang & Fengxia Hao, 2017. "Optimization for the Locations of Ambulances under Two-Stage Life Rescue in the Emergency Medical Service: A Case Study in Shanghai, China," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-14, August.
  • Handle: RePEc:hin:jnlmpe:1830480
    DOI: 10.1155/2017/1830480
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    Cited by:

    1. 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.

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