Designing Robust Coverage Systems: A Maximal Covering Model with Geographically Varying Failure Probabilities.
Covering models have been used in a wide range of modeling and geospatial analysis applications ranging from planning emergency services to natural reserve design. One topic in coverage modeling that has received considerable research attention is addressing uncertainty due to facility unavailabilit...
| Published in: | Annals of the Association of American Geographers Vol. 104; no. 5; pp. 922 - 939 |
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| Main Authors: | , , |
| Format: | Article |
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Taylor & Francis Ltd
Sep2014
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=97424593&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 97424593 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00045608 AAG jtl: Annals of the Association of American Geographers issn: 00045608 maglogo: Y pubinfo: dt: Sep2014 vid: 104 iid: 5 pid: 377 pub: Taylor & Francis Ltd artinfo: ui: 97424593 10.1080/00045608.2014.923722 ppf: 922 ppct: 17 formats: tig: atl: Designing Robust Coverage Systems: A Maximal Covering Model with Geographically Varying Failure Probabilities. aug: au: Lei, Ting L. Tong, Daoqin Church, Richard L. affil: Department of Geography, University of Santa Barbara School of Geography and Development, University of Arizona su: Emergency management Spatial systems Spatial variation sug: subj: Emergency management Other federal protective services Other Justice, Public Order, and Safety Activities Other municipal protective services Other provincial protective services Emergency and Other Relief Services Spatial systems Spatial variation keyword: coverage network location analysis resilient design spatial optimization system vulnerability análisis locacional análisis locacional diseño resiliente diseño resiliente optimización espacial optimización espacial red de cobertura vulnerabilidad del sistema 区位分析 恢復性设计 空间优化 系统脆弱性 覆盖网 coverage network location analysis resilient design spatial optimization system vulnerability análisis locacional análisis locacional diseño resiliente diseño resiliente optimización espacial optimización espacial red de cobertura vulnerabilidad del sistema 区位分析 恢復性设计 空间优化 系统脆弱性 覆盖网 ab: Covering models have been used in a wide range of modeling and geospatial analysis applications ranging from planning emergency services to natural reserve design. One topic in coverage modeling that has received considerable research attention is addressing uncertainty due to facility unavailability and service disruptions. In this article, we propose a covering model that maximizes the expected coverage of demand by considering the possibility of facility failures. Unlike existing models that assume a uniform failure probability across all sites in an area, the proposed model can account for spatially varying failure probabilities and describes better the underlying geographic processes that cause facility failures. The model is posed as a spatial optimization problem using integer linear programming. We compare two different formulations of the covering model and discuss their properties. The proposed model formulations have been tested computationally using a warning sirens data set that has been widely used in assessing covering models. We conclude with a summary of findings as well as possible directions of future research. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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