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Conference Paper: A Real-Time Decision Support Tool for Disaster Response: A Mathematical Programming Approach

TitleA Real-Time Decision Support Tool for Disaster Response: A Mathematical Programming Approach
Authors
Keywordsreal-Time disaster data
optimization
mathematical modeling
emergency supplies
disaster response
mixed-integer linear programming
humanitarian logistics
Issue Date2015
Citation
Proceedings - 2015 IEEE International Congress on Big Data, BigData Congress 2015, 2015, p. 639-642 How to Cite?
Abstract© 2015 IEEE. Disasters are sudden and calamitous events that can cause severe and pervasive negative impacts on society and huge human losses. Governments and humanitarian organizations have been putting tremendous efforts to avoid and reduce the negative consequences due to disasters. In recent years, information technology and big data have played an important role in disaster management. While there has been much work on disaster information extraction and dissemination, real-Time optimization for decision support for disaster response is rarely addressed in big data research. In this paper, we propose a mathematical programming approach, with real-Time disaster-related information, to optimize the post-disaster decisions for emergency supplies delivery. This decision support tool can provide rapid and effective solutions, which are essential for disaster response.
Persistent Identifierhttp://hdl.handle.net/10722/246834
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorKuo, Yong Hong-
dc.contributor.authorLeung, Janny M.Y.-
dc.contributor.authorMeng, Helen M.-
dc.contributor.authorTsoi, Kelvin K.F.-
dc.date.accessioned2017-09-26T04:28:07Z-
dc.date.available2017-09-26T04:28:07Z-
dc.date.issued2015-
dc.identifier.citationProceedings - 2015 IEEE International Congress on Big Data, BigData Congress 2015, 2015, p. 639-642-
dc.identifier.urihttp://hdl.handle.net/10722/246834-
dc.description.abstract© 2015 IEEE. Disasters are sudden and calamitous events that can cause severe and pervasive negative impacts on society and huge human losses. Governments and humanitarian organizations have been putting tremendous efforts to avoid and reduce the negative consequences due to disasters. In recent years, information technology and big data have played an important role in disaster management. While there has been much work on disaster information extraction and dissemination, real-Time optimization for decision support for disaster response is rarely addressed in big data research. In this paper, we propose a mathematical programming approach, with real-Time disaster-related information, to optimize the post-disaster decisions for emergency supplies delivery. This decision support tool can provide rapid and effective solutions, which are essential for disaster response.-
dc.languageeng-
dc.relation.ispartofProceedings - 2015 IEEE International Congress on Big Data, BigData Congress 2015-
dc.subjectreal-Time disaster data-
dc.subjectoptimization-
dc.subjectmathematical modeling-
dc.subjectemergency supplies-
dc.subjectdisaster response-
dc.subjectmixed-integer linear programming-
dc.subjecthumanitarian logistics-
dc.titleA Real-Time Decision Support Tool for Disaster Response: A Mathematical Programming Approach-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/BigDataCongress.2015.98-
dc.identifier.scopuseid_2-s2.0-84959571449-
dc.identifier.spage639-
dc.identifier.epage642-
dc.identifier.isiWOS:000380443700088-

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