A dynamic evacuation network optimization problem with lane reversal and crossing elimination strategies
AbstractThis paper discusses a dynamic evacuation network optimization problem that incorporates lane reversal and crossing elimination strategies. These two lane-based planning strategies complement one another by increasing capacity in specific directions through the evacuation network. A bi-level network optimization model is formulated, in which the upper level aims at optimizing the network evacuation performance subject to the lane-reversal and crossing-elimination constraints and the lower level conveys a cell transmission-based dynamic traffic assignment problem. An integrated Lagrangian relaxation and tabu search method is devised for approximating optimal problem solutions through an iterative optimization-evaluation process. The numerical results of implementing the developed modeling and solution approach to a synthetic network and a real-world example application justify its theoretical and practical value.
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Bibliographic InfoArticle provided by Elsevier in its journal Transportation Research Part E: Logistics and Transportation Review.
Volume (Year): 46 (2010)
Issue (Month): 3 (May)
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description
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- Ben-Tal, Aharon & Chung, Byung Do & Mandala, Supreet Reddy & Yao, Tao, 2011. "Robust optimization for emergency logistics planning: Risk mitigation in humanitarian relief supply chains," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1177-1189, September.
- Shahriar Afandizadeh & Arash Jahangiri & Navid Kalantari, 2013. "Identifying the optimal configuration of one-way and two-way streets for contraflow operation during an emergency evacuation," Natural Hazards, International Society for the Prevention and Mitigation of Natural Hazards, vol. 69(3), pages 1315-1334, December.
- Bretschneider, S. & Kimms, A., 2012. "Pattern-based evacuation planning for urban areas," European Journal of Operational Research, Elsevier, vol. 216(1), pages 57-69.
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