Locating an ambulance base by using social media: a case study in Bangkok

Suriyaphong Nilsang, Chumpol Yuangyai (), Chen-Yang Cheng and Udom Janjarassuk
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Suriyaphong Nilsang: King Mongkut’s Institute of Technology Ladkrabang
Chumpol Yuangyai: King Mongkut’s Institute of Technology Ladkrabang
Chen-Yang Cheng: National Taipei University of Technology
Udom Janjarassuk: King Mongkut’s Institute of Technology Ladkrabang

Annals of Operations Research, 2019, vol. 283, issue 1, No 21, 497-516

Abstract: Abstract Response time reduction is a fundamental aspect of ambulance location management. To minimize patient mortality and disability, the response time of emergency medical services is critical. Therefore, real-time management is required to determine the location of an ambulance with a low response time or called or a dynamic allocation system. Dynamic allocation is moving the ambulance bases from low demand areas to high-demand areas that is useful in the operational level. However, the dynamic allocation model for real-time management requires re-allocation of ambulances, resulting in high costs and heavy workloads for the ambulance crews. This paper focuses on a covering model based on social media analysis. The model was used for developing an ambulance reallocation system. In addition to dynamic allocation, the proposed model considers real-time data from a social media application (Twitter) to minimize the response time and cost during emergencies and disasters. Twitter has been used in various ways to communicate during and manage emergencies. In this paper, we formulate the Maximal Covering Location Problem (MCLP), develop a solution procedure based on social media (Twitter application) and show the effect of the approach on the optimal solution by comparing it with the classical approach and also demonstrate our approach on Bangkok EMS.

Keywords: Emergency medical service; Social media information; Control charts; Covering model; Sensitivity analysis (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s10479-018-2918-8

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