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- Publisher Website: 10.1109/BigDataCongress.2015.98
- Scopus: eid_2-s2.0-84959571449
- WOS: WOS:000380443700088
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Conference Paper: A Real-Time Decision Support Tool for Disaster Response: A Mathematical Programming Approach
Title | A Real-Time Decision Support Tool for Disaster Response: A Mathematical Programming Approach |
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Authors | |
Keywords | real-Time disaster data optimization mathematical modeling emergency supplies disaster response mixed-integer linear programming humanitarian logistics |
Issue Date | 2015 |
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 Identifier | http://hdl.handle.net/10722/246834 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Kuo, Yong Hong | - |
dc.contributor.author | Leung, Janny M.Y. | - |
dc.contributor.author | Meng, Helen M. | - |
dc.contributor.author | Tsoi, Kelvin K.F. | - |
dc.date.accessioned | 2017-09-26T04:28:07Z | - |
dc.date.available | 2017-09-26T04:28:07Z | - |
dc.date.issued | 2015 | - |
dc.identifier.citation | Proceedings - 2015 IEEE International Congress on Big Data, BigData Congress 2015, 2015, p. 639-642 | - |
dc.identifier.uri | http://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.language | eng | - |
dc.relation.ispartof | Proceedings - 2015 IEEE International Congress on Big Data, BigData Congress 2015 | - |
dc.subject | real-Time disaster data | - |
dc.subject | optimization | - |
dc.subject | mathematical modeling | - |
dc.subject | emergency supplies | - |
dc.subject | disaster response | - |
dc.subject | mixed-integer linear programming | - |
dc.subject | humanitarian logistics | - |
dc.title | A Real-Time Decision Support Tool for Disaster Response: A Mathematical Programming Approach | - |
dc.type | Conference_Paper | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/BigDataCongress.2015.98 | - |
dc.identifier.scopus | eid_2-s2.0-84959571449 | - |
dc.identifier.spage | 639 | - |
dc.identifier.epage | 642 | - |
dc.identifier.isi | WOS:000380443700088 | - |