Risk-averse ambulance redeployment via multi-armed bandits

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dc.citation.epage4en_US
dc.citation.spage1en_US
dc.contributor.authorSahin, U.en_US
dc.contributor.authorYucesoy, V.en_US
dc.contributor.authorKoc, A.en_US
dc.contributor.authorTekin, Cemen_US
dc.coverage.spatialIzmir, Turkeyen_US
dc.date.accessioned2019-02-21T16:04:57Z
dc.date.available2019-02-21T16:04:57Z
dc.date.issued2018en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.descriptionDate of Conference: 2-5 May 2018en_US
dc.description.abstractAmbulance redeployment comprises the problem of deploying ambulances to certain locations in order to minimize the arrival times to possible calls and plays a significant role in improving a country's emergency medical services and increasing the number of lives saved during an emergency. In this study, unlike the existing optimization methods in the literature, the problem is cast as a multi-armed bandit problem. Multi-armed bandit problems are a part of sequential online learning methods and utilized in maximizing a gain function (i.e. reward) when the reward distributions are unknown. In this study, in addition to the objective of maximizing rewards, the objective of minimizing the expected variance of rewards is also considered. The effect of risk taken by the system on average arrival times and number of calls responded on time is investigated. Ambulance redeployment is performed by a risk-averse multi-armed bandit algorithm on a data-driven simulator. As a result, it is shown that the algorithm which takes less risk (i.e. that minimizes the variance of response times) responds to more cases on time.
dc.identifier.doi10.1109/SIU.2018.8404439
dc.identifier.isbn9781538615010
dc.identifier.urihttp://hdl.handle.net/11693/50221
dc.language.isoTurkish
dc.publisherIEEEen_US
dc.relation.isversionofhttps://doi.org/10.1109/SIU.2018.8404439
dc.source.title2018 26th Signal Processing and Communications Applications Conference (SIU)en_US
dc.subjectAmbulance redeploymenten_US
dc.subjectMulti-armed bandit problemsen_US
dc.subjectRisk minimizationen_US
dc.titleRisk-averse ambulance redeployment via multi-armed banditsen_US
dc.title.alternativeÇok kollu haydutlar ile riskten kaçınan ambulans konumlandırmasıen_US
dc.typeConference Paperen_US
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