TY - JOUR
T1 - A dynamic evacuation network optimization problem with lane reversal and crossing elimination strategies
AU - Xie, Chi
AU - Lin, Dung Ying
AU - Travis Waller, S.
N1 - Funding Information:
The authors are indebted to Professor Mark Turnquist of Cornell University for his valuable suggestions at the early stage of this research and to Professor Shashi Shekhar of the University of Minnesota who provided the Monticello network data set used in the case study. The second author would like to acknowledge the National Research Council, Taiwan, ROC for providing partial funding support under the project of No. NSC 98-2410-H-006-119. The Editor-in-Chief, Professor Wayne Talley and an anonymous reviewer’s constructive suggestions greatly improve the quality of the paper. However, the contents of this paper reflect only the view of the authors, who are solely responsible for the facts and the accuracy of the data presented herein.
PY - 2010/5
Y1 - 2010/5
N2 - 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.
AB - 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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U2 - 10.1016/j.tre.2009.11.004
DO - 10.1016/j.tre.2009.11.004
M3 - Article
AN - SCOPUS:74449091182
VL - 46
SP - 295
EP - 316
JO - Transportation Research, Part E: Logistics and Transportation Review
JF - Transportation Research, Part E: Logistics and Transportation Review
SN - 1366-5545
IS - 3
ER -