完整後設資料紀錄
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dc.contributor.authorFeng, CMen_US
dc.contributor.authorWen, CCen_US
dc.date.accessioned2014-12-08T15:25:15Z-
dc.date.available2014-12-08T15:25:15Z-
dc.date.issued2005en_US
dc.identifier.issn1348-5393en_US
dc.identifier.urihttp://hdl.handle.net/11536/17631-
dc.description.abstractWhen a severe earthquake takes place, the road network system often suffers serious destruction and results in the malfunctioning of lifeline network systems. In particular, impassable roads and streets block transportation in evacuation, rescue and restoration. How to maintain traffic functions to facilitate rescue missions and save more lives turns out to be an essential task during the post-quake period. This paper aims at developing a decision-making tool that can potentially be used in managing the emergency vehicles and controlling the private vehicle flows in earthquake disasters. Methodologically, the problem to be addressed is formulated as a multi-commodity, two-modal network flow problem based on the concept of bi-level programming and network optimization theory. To prove the feasibility, this paper has conducted a numerical case study using a small sample data from the earthquake-raided areas. To solve the model efficiently, the genetic algorithm (GA) been applied to solve the model. A numerical example shows that this study can create an effective way to implement traffic regulation during earthquake disaster.en_US
dc.language.isoen_USen_US
dc.subjecttraffic demand managementen_US
dc.subjectbi-level programmingen_US
dc.subjectemergency vehiclesen_US
dc.subjectgenetic algorithmen_US
dc.subjectCDA (combined distribution/assignment model)en_US
dc.titleA bi-level programming model for allocating private and emergency vehicle flows in seismic disaster areasen_US
dc.typeProceedings Paperen_US
dc.identifier.journalProceedings of the Eastern Asia Society for Transportation Studies, Vol 5en_US
dc.citation.volume5en_US
dc.citation.spage1408en_US
dc.citation.epage1423en_US
dc.contributor.department運輸與物流管理系 註:原交通所+運管所zh_TW
dc.contributor.departmentDepartment of Transportation and Logistics Managementen_US
dc.identifier.wosnumberWOS:000236346601046-
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