Sequential sensor installation for wiener disorder detection

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dc.citation.epage850en_US
dc.citation.issueNumber3en_US
dc.citation.spage827en_US
dc.citation.volumeNumber41en_US
dc.contributor.authorDayanik, S.en_US
dc.contributor.authorSezer, S. O.en_US
dc.date.accessioned2018-04-12T11:00:47Z
dc.date.available2018-04-12T11:00:47Z
dc.date.issued2016en_US
dc.departmentDepartment of Industrial Engineeringen_US
dc.departmentDepartment of Mathematicsen_US
dc.description.abstractWe consider a centralized multisensor online quickest disorder detection problem where the observation from each sensor is a Wiener process gaining a constant drift at a common unobservable disorder time. The objective is to detect the disorder time as quickly as possible with small probability of false alarms. Unlike the earlier work on multisensor change detection problems, we assume that the observer can apply a sequential sensor installation policy. At any time before a disorder alarm is raised, the observer can install new sensors to collect additional signals. The sensors are statistically identical, and there is a fixed installation cost per sensor. We propose a Bayesian formulation of the problem. We identify an optimal policy consisting of a sequential sensor installation strategy and an alarm time, which minimize a linear Bayes risk of detection delay, false alarm, and new sensor installations. We also provide a numerical algorithm and illustrate it on examples. Our numerical examples show that significant reduction in the Bayes risk can be attained compared to the case where we apply a static sensor policy only. In some examples, the optimal sequential sensor installation policy starts with 30% less number of sensors than the optimal static sensor installation policy and the total percentage savings reach to 12%.en_US
dc.identifier.doi10.1287/moor.2015.0756en_US
dc.identifier.eissn1526-5471
dc.identifier.issn0364-765X
dc.identifier.urihttp://hdl.handle.net/11693/37031
dc.language.isoEnglishen_US
dc.publisherInstitute for Operations Research and the Management Sciences (I N F O R M S)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1287/moor.2015.0756en_US
dc.source.titleMathematics of Operations Researchen_US
dc.subjectMultisensor sequential change detectionen_US
dc.subjectOptimal multiple stoppingen_US
dc.subjectWiener disorder problemen_US
dc.subjectAlgorithmsen_US
dc.subjectBayesian networksen_US
dc.subjectErrorsen_US
dc.subjectSignal detectionen_US
dc.subjectBayesian formulationen_US
dc.subjectFixed installationsen_US
dc.subjectMultiple stoppingen_US
dc.subjectNumerical algorithmsen_US
dc.subjectProbability of false alarmen_US
dc.subjectSensor installationen_US
dc.subjectSequential change detectionen_US
dc.subjectWiener disorder problemen_US
dc.subjectAlarm systemsen_US
dc.titleSequential sensor installation for wiener disorder detectionen_US
dc.typeArticleen_US
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