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Time-Dependent Ambulance Deployment and Shift Scheduling of Crews

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Operations Research Proceedings 2015

Part of the book series: Operations Research Proceedings ((ORP))

Abstract

For patients requesting emergency medical services (EMS) in a life-threatening emergency, the probability of survival is strongly related to the rapidness of assistance. An especially challenging task for planners is to allocate limited resources while managing increasing demand for services. The provision of sufficient staff resources for the ambulances has great impact on the initial treatment of patients and thus on the quality of emergency services. Data-driven empirically required ambulance location planning as well as the allocation of staff for these vehicles are successively optimized in the proposed approach to support emergency medical service decision makers. According to the identified problem structure, an integer linear programming model is proposed. An exemplary case study based on real-world data demonstrates how this approach can be used within the emergency medical service planning process.

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Author information

Authors and Affiliations

  1. Chair for Management, Faculty of Management and Economics, esp. Operations Research and Accounting, Ruhr University Bochum, Bochum, Germany

    Lara Wiesche

Authors
  1. Lara Wiesche
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Correspondence to Lara Wiesche .

Editor information

Editors and Affiliations

  1. Department of Business Administration, University of Vienna, Vienna, Austria

    Karl Franz Dörner

  2. Decision Sciences and Statistics (IDS) Department, ESSEC Business School of Paris, Cergy Pontoise Cedex, France

    Ivana Ljubic

  3. Department of Statistics and Operations Research, University of Vienna, Vienna, Austria

    Georg Pflug

  4. Operations Research and Control Systems, TU Wien, Vienna, Austria

    Gernot Tragler

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Wiesche, L. (2017). Time-Dependent Ambulance Deployment and Shift Scheduling of Crews. In: Dörner, K., Ljubic, I., Pflug, G., Tragler, G. (eds) Operations Research Proceedings 2015. Operations Research Proceedings. Springer, Cham. https://doi.org/10.1007/978-3-319-42902-1_80

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