Dynamic Route Network Planning Problem for Emergency Evacuation in Restricted-Space Scenarios
The authors investigate a dynamic route planning problem in restricted-space evacuation, namely, the Multiobjective Dynamic Route Network Planning (MODRNP) problem. It models the multisource to multidestination evacuation in restricted-space scenarios, with the objectives of minimizing the whole evacuation delay and maximizing the evacuation efficiency. The authors study the problem in 3D scenarios, which can provide intuition vision for the geographic space and contribute to the evacuation plan and implementation. Based on the auxiliary graph transformation, the authors propose a heuristic algorithm referred to the classical problem, Minimum Weighted Set Cover. The authors finally conduct extensive experiments to evaluate the performance of the proposed algorithm and give an application instance on a typical kind of restricted-space scenarios. The results indicate that the proposed algorithm outperforms the existing alternatives in terms of the utilization as well as timeliness.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/oclc/5121625
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Supplemental Notes:
- © 2018 Yi Hong, et al.
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Authors:
- Hong, Yi
- Li, Deying
- Wu, Qiang
- Xu, Hua
- Publication Date: 2018
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: 13p
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Serial:
- Journal of Advanced Transportation
- Volume: 2018
- Issue Number: Article ID 4295419
- Publisher: John Wiley & Sons, Incorporated
- ISSN: 0197-6729
- EISSN: 2042-3195
- Serial URL: http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2042-3195
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Publication flags:
Open Access (libre)
Subject/Index Terms
- TRT Terms: Algorithms; Disaster preparedness; Evacuation; Heuristic methods; Routes and routing; Traffic congestion; Traffic delays
- Subject Areas: Highways; Operations and Traffic Management; Safety and Human Factors; Security and Emergencies;
Filing Info
- Accession Number: 01676007
- Record Type: Publication
- Files: TRIS
- Created Date: Jul 25 2018 9:21AM