A dynamic evacuation network optimization problem with lane reversal and crossing elimination strategies

This 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...

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Bibliographic Details
Published inTransportation research. Part E, Logistics and transportation review Vol. 46; no. 3; pp. 295 - 316
Main Authors Xie, Chi, Lin, Dung-Ying, Travis Waller, S.
Format Journal Article
LanguageEnglish
Published Exeter Elsevier India Pvt Ltd 01.05.2010
Elsevier
Elsevier Sequoia S.A
SeriesTransportation Research Part E: Logistics and Transportation Review
Subjects
Assignment problem
Cell transmission model
Dynamic traffic assignment
Dynamics
Evacuation
Evacuation planning
Evacuation planning Transportation network design Lagrangian relaxation Tabu search Dynamic traffic assignment Cell transmission model
Evacuations & rescues
Lagrange multiplier
Lagrangian relaxation
Lanes
Mathematical models
Network management systems
Networks
Optimization
Optimization algorithms
Strategy
Studies
Tabu search
Traffic assignment
Traffic flow
Transportation
Transportation network design
Transportation network design
Tabu search
Dynamic traffic assignment
Evacuation planning
Lagrangian relaxation
Cell transmission model
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Summary:This 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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ISSN:1366-5545
1878-5794
DOI:10.1016/j.tre.2009.11.004