Risk based Optimization for Improving Emergency Medical Systems

In emergency medical systems, arriving at the incident location a few seconds early can save a human life. Thus, this paper is motivated by the need to reduce the response time – time taken to arrive at the incident location after receiving the emergency call – of Emergency Response Vehicles, ERVs (...

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Main Authors: SAISUBRAMANIAN, Sandhya, Pradeep VARAKANTHAM, LAU, Hoong Chuin
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Language:English
Published: Institutional Knowledge at Singapore Management University 2015
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Online Access:https://ink.library.smu.edu.sg/sis_research/2850
https://ink.library.smu.edu.sg/context/sis_research/article/3850/viewcontent/C127___Risk_based_Optimization_for_Improving_Emergency_Medical_Systems__AAAI2015_.pdf
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spelling sg-smu-ink.sis_research-38502018-07-13T04:14:55Z Risk based Optimization for Improving Emergency Medical Systems SAISUBRAMANIAN, Sandhya Pradeep VARAKANTHAM, LAU, Hoong Chuin In emergency medical systems, arriving at the incident location a few seconds early can save a human life. Thus, this paper is motivated by the need to reduce the response time – time taken to arrive at the incident location after receiving the emergency call – of Emergency Response Vehicles, ERVs (ex: ambulances, fire rescue vehicles) for as many requests as possible. We expect to achieve this primarily by positioning the "right" number of ERVs at the "right" places and at the "right" times. Given the exponentially large action space (with respect to number of ERVs and their placement) and the stochasticity in location and timing of emergency incidents, this problem is computationally challenging. To that end, our contributions building on existing data-driven approaches are three fold. Finally, we provide an exhaustive evaluation on real-world datasets from two asian cities that demonstrates the improvement provided by our approach over current practice and the best known approach from literature. 2015-01-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/2850 https://ink.library.smu.edu.sg/context/sis_research/article/3850/viewcontent/C127___Risk_based_Optimization_for_Improving_Emergency_Medical_Systems__AAAI2015_.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Computer Sciences Health and Medical Administration Operations Research, Systems Engineering and Industrial Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Computer Sciences
Health and Medical Administration
Operations Research, Systems Engineering and Industrial Engineering
spellingShingle Computer Sciences
Health and Medical Administration
Operations Research, Systems Engineering and Industrial Engineering
SAISUBRAMANIAN, Sandhya
Pradeep VARAKANTHAM,
LAU, Hoong Chuin
Risk based Optimization for Improving Emergency Medical Systems
description In emergency medical systems, arriving at the incident location a few seconds early can save a human life. Thus, this paper is motivated by the need to reduce the response time – time taken to arrive at the incident location after receiving the emergency call – of Emergency Response Vehicles, ERVs (ex: ambulances, fire rescue vehicles) for as many requests as possible. We expect to achieve this primarily by positioning the "right" number of ERVs at the "right" places and at the "right" times. Given the exponentially large action space (with respect to number of ERVs and their placement) and the stochasticity in location and timing of emergency incidents, this problem is computationally challenging. To that end, our contributions building on existing data-driven approaches are three fold. Finally, we provide an exhaustive evaluation on real-world datasets from two asian cities that demonstrates the improvement provided by our approach over current practice and the best known approach from literature.
format text
author SAISUBRAMANIAN, Sandhya
Pradeep VARAKANTHAM,
LAU, Hoong Chuin
author_facet SAISUBRAMANIAN, Sandhya
Pradeep VARAKANTHAM,
LAU, Hoong Chuin
author_sort SAISUBRAMANIAN, Sandhya
title Risk based Optimization for Improving Emergency Medical Systems
title_short Risk based Optimization for Improving Emergency Medical Systems
title_full Risk based Optimization for Improving Emergency Medical Systems
title_fullStr Risk based Optimization for Improving Emergency Medical Systems
title_full_unstemmed Risk based Optimization for Improving Emergency Medical Systems
title_sort risk based optimization for improving emergency medical systems
publisher Institutional Knowledge at Singapore Management University
publishDate 2015
url https://ink.library.smu.edu.sg/sis_research/2850
https://ink.library.smu.edu.sg/context/sis_research/article/3850/viewcontent/C127___Risk_based_Optimization_for_Improving_Emergency_Medical_Systems__AAAI2015_.pdf
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