Bounded rank optimization for effective and efficient emergency response

Effective placement of emergency response vehicles (such as ambulances, fire trucks, police cars) to deal with medical, fire or criminal activities can reduce the incident response time by few seconds, which in turn can potentially save a human life. Owing to its adoption in Emergency Medical Servic...

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Main Authors: MANOHAR, Pallavi Madhusudan, VARAKANTHAM, Pradeep, LAU, Hoong Chuin
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Language:English
Published: Institutional Knowledge at Singapore Management University 2018
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Online Access:https://ink.library.smu.edu.sg/sis_research/4286
https://ink.library.smu.edu.sg/context/sis_research/article/5289/viewcontent/ICAPS18_Bounded_Rank_Optimization_for_Effective_and_Efficient_Emergency_Response.pdf
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spelling sg-smu-ink.sis_research-52892019-02-21T08:28:21Z Bounded rank optimization for effective and efficient emergency response MANOHAR, Pallavi Madhusudan VARAKANTHAM, Pradeep LAU, Hoong Chuin Effective placement of emergency response vehicles (such as ambulances, fire trucks, police cars) to deal with medical, fire or criminal activities can reduce the incident response time by few seconds, which in turn can potentially save a human life. Owing to its adoption in Emergency Medical Services (EMSs) worldwide, existing research on improving emergency response has focused on optimizing the objective of bounded time (i.e. number of incidents served in a fixed time). Due to the dependence of this objective on temporal uncertainty, optimizing the bounded time objective is challenging. In this paper, we propose a new objective referred to as the bounded rank (which is the number of incidents served by a base station whose rank is below a bounded rank value) that has nice theoretical properties and serves as an indirect substitute for the bounded time objective. To understand the theoretical properties of this new objective in the context of the spatio-temporal uncertainty associated with emergency incidents, we first provide a Poisson Point Process (PPP) model of the emergency response problem. We then formally define the bounded rank objective in the context of the model and demonstrate that the bounded rank metric is monotone submodular. Due to the monotone submodularity of the objective, we can propose a greedy approach that can provide an a priori guarantee of 50% from optimal and a much tighter posteriori guarantee. Practically and more importantly, we demonstrate that optimizing this bounded rank objective on simulators validated on real data (and not just on the abstract PPP model) provides better results than the best known approach for optimizing bounded time objective. 2018-06-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/4286 https://ink.library.smu.edu.sg/context/sis_research/article/5289/viewcontent/ICAPS18_Bounded_Rank_Optimization_for_Effective_and_Efficient_Emergency_Response.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 Emergency response Submodularity Bounded rank optimization Emergency medical services Greedy approaches Incident response Poisson point process Spatio temporal Temporal uncertainty Medicine and Health Sciences Operations Research, Systems Engineering and Industrial Engineering Transportation
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Emergency response
Submodularity
Bounded rank optimization
Emergency medical services
Greedy approaches
Incident response
Poisson point process
Spatio temporal
Temporal uncertainty
Medicine and Health Sciences
Operations Research, Systems Engineering and Industrial Engineering
Transportation
spellingShingle Emergency response
Submodularity
Bounded rank optimization
Emergency medical services
Greedy approaches
Incident response
Poisson point process
Spatio temporal
Temporal uncertainty
Medicine and Health Sciences
Operations Research, Systems Engineering and Industrial Engineering
Transportation
MANOHAR, Pallavi Madhusudan
VARAKANTHAM, Pradeep
LAU, Hoong Chuin
Bounded rank optimization for effective and efficient emergency response
description Effective placement of emergency response vehicles (such as ambulances, fire trucks, police cars) to deal with medical, fire or criminal activities can reduce the incident response time by few seconds, which in turn can potentially save a human life. Owing to its adoption in Emergency Medical Services (EMSs) worldwide, existing research on improving emergency response has focused on optimizing the objective of bounded time (i.e. number of incidents served in a fixed time). Due to the dependence of this objective on temporal uncertainty, optimizing the bounded time objective is challenging. In this paper, we propose a new objective referred to as the bounded rank (which is the number of incidents served by a base station whose rank is below a bounded rank value) that has nice theoretical properties and serves as an indirect substitute for the bounded time objective. To understand the theoretical properties of this new objective in the context of the spatio-temporal uncertainty associated with emergency incidents, we first provide a Poisson Point Process (PPP) model of the emergency response problem. We then formally define the bounded rank objective in the context of the model and demonstrate that the bounded rank metric is monotone submodular. Due to the monotone submodularity of the objective, we can propose a greedy approach that can provide an a priori guarantee of 50% from optimal and a much tighter posteriori guarantee. Practically and more importantly, we demonstrate that optimizing this bounded rank objective on simulators validated on real data (and not just on the abstract PPP model) provides better results than the best known approach for optimizing bounded time objective.
format text
author MANOHAR, Pallavi Madhusudan
VARAKANTHAM, Pradeep
LAU, Hoong Chuin
author_facet MANOHAR, Pallavi Madhusudan
VARAKANTHAM, Pradeep
LAU, Hoong Chuin
author_sort MANOHAR, Pallavi Madhusudan
title Bounded rank optimization for effective and efficient emergency response
title_short Bounded rank optimization for effective and efficient emergency response
title_full Bounded rank optimization for effective and efficient emergency response
title_fullStr Bounded rank optimization for effective and efficient emergency response
title_full_unstemmed Bounded rank optimization for effective and efficient emergency response
title_sort bounded rank optimization for effective and efficient emergency response
publisher Institutional Knowledge at Singapore Management University
publishDate 2018
url https://ink.library.smu.edu.sg/sis_research/4286
https://ink.library.smu.edu.sg/context/sis_research/article/5289/viewcontent/ICAPS18_Bounded_Rank_Optimization_for_Effective_and_Efficient_Emergency_Response.pdf
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