Determining optimal treatment rate after a disaster

dc.contributor.author Kilic, Asli
dc.contributor.author Dincer, M. Cemali
dc.contributor.author Gökçe, Mahmut Ali
dc.date.accessioned 2023-06-16T14:18:41Z
dc.date.available 2023-06-16T14:18:41Z
dc.date.issued 2014
dc.description.abstract From the standpoint of medical services, a disaster is a calamitous event resulting in an unexpected number of casualties that exceeds the therapeutic capacities of medical services. In these situations, effective medical response plays a crucial role in saving life. To model medical rescue activities, a two-priority non-preemptive S-server, and a finite capacity queueing system is considered. After constructing Chapman-Kolmogorov differential equations, Pontryagin's minimum principle is used to calculate optimal treatment rates for each priority class. The performance criterion is to minimize both the expected value of the square of the difference between the number of servers and the number of patients in the system, and also the cost of serving these patients over a determined time period. The performance criterion also includes a final time cost related to deviations from the determined value of the desired queue length. The two point boundary value problem is numerically solved for different arrival rate patterns and selected parameters. en_US
dc.identifier.doi 10.1057/jors.2013.52
dc.identifier.issn 0160-5682
dc.identifier.issn 1476-9360
dc.identifier.scopus 2-s2.0-84902132799
dc.identifier.uri https://doi.org/10.1057/jors.2013.52
dc.identifier.uri https://hdl.handle.net/20.500.14365/1533
dc.language.iso en en_US
dc.publisher Taylor & Francis Ltd en_US
dc.relation.ispartof Journal of the Operatıonal Research Socıety en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject queueing en_US
dc.subject optimization en_US
dc.subject Markov processes en_US
dc.subject health service en_US
dc.subject Queuing-Problems en_US
dc.subject Simulation en_US
dc.subject Triage en_US
dc.subject Earthquake en_US
dc.subject Principles en_US
dc.subject Operations en_US
dc.subject Allocation en_US
dc.subject Balking en_US
dc.subject System en_US
dc.subject Model en_US
dc.title Determining optimal treatment rate after a disaster en_US
dc.type Article en_US
dspace.entity.type Publication
gdc.author.id KILIC, ASLI/0000-0002-3926-8608
gdc.author.scopusid 56199516700
gdc.author.scopusid 57196790124
gdc.author.scopusid 36484461000
gdc.author.wosid KILIC, ASLI/AAG-8033-2021
gdc.bip.impulseclass C4
gdc.bip.influenceclass C4
gdc.bip.popularityclass C4
gdc.coar.access metadata only access
gdc.coar.type text::journal::journal article
gdc.collaboration.industrial false
gdc.description.department İzmir Ekonomi Üniversitesi en_US
gdc.description.departmenttemp [Kilic, Asli] Ege Univ, Dept Stat, TR-35100 Bornova, Turkey; [Dincer, M. Cemali; Gökçe, Mahmut Ali] Izmir Univ Econ, Dept Ind Syst Engn, Izmir, Turkey en_US
gdc.description.endpage 1067 en_US
gdc.description.issue 7 en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q1
gdc.description.startpage 1053 en_US
gdc.description.volume 65 en_US
gdc.description.wosquality Q2
gdc.identifier.openalex W1969293579
gdc.identifier.wos WOS:000337499700005
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gdc.oaire.diamondjournal false
gdc.oaire.impulse 5.0
gdc.oaire.influence 3.2775243E-9
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gdc.oaire.keywords queueing
gdc.oaire.keywords Markov processes
gdc.oaire.keywords health service
gdc.oaire.keywords optimization
gdc.oaire.popularity 6.2876353E-9
gdc.oaire.publicfunded false
gdc.oaire.sciencefields 0211 other engineering and technologies
gdc.oaire.sciencefields 0202 electrical engineering, electronic engineering, information engineering
gdc.oaire.sciencefields 02 engineering and technology
gdc.openalex.collaboration National
gdc.openalex.fwci 2.00177118
gdc.openalex.normalizedpercentile 0.88
gdc.opencitations.count 16
gdc.plumx.crossrefcites 7
gdc.plumx.mendeley 32
gdc.plumx.scopuscites 15
gdc.scopus.citedcount 15
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