TY - JOUR
T1 - Evacuation Planning with Endogenous Transportation Network Degradations
T2 - A Stochastic Cell-Based Model and Solution Procedure
AU - Li, Jian
AU - Ozbay, Kaan
N1 - Publisher Copyright:
© 2014, Springer Science+Business Media New York.
PY - 2014/4/23
Y1 - 2014/4/23
N2 - Capturing the impact of uncertain events in emergency evacuation time estimation is an important issue for public officials to avoid unexpected delays and related losses of life and property. However, most of the current studies in evacuation planning only focus on exogenous uncertainties, such as flooding damage in a hurricane, but ignore uncertainties caused by endogenously determined risks, or so called flow-related risks. This paper proposes an analytical framework along with an efficient solution methodology to evaluate the impact of endogenously determined risks in order to estimate evacuation time. We incorporate the probability function of endogenously determined risks in a cell-based macroscopic evacuation model. A network flow algorithm based on the sample average approximation approach is used as part of the solution procedure. Finally, a sample network is used to demonstrate the salient features of the proposed stochastic model and solution procedure.
AB - Capturing the impact of uncertain events in emergency evacuation time estimation is an important issue for public officials to avoid unexpected delays and related losses of life and property. However, most of the current studies in evacuation planning only focus on exogenous uncertainties, such as flooding damage in a hurricane, but ignore uncertainties caused by endogenously determined risks, or so called flow-related risks. This paper proposes an analytical framework along with an efficient solution methodology to evaluate the impact of endogenously determined risks in order to estimate evacuation time. We incorporate the probability function of endogenously determined risks in a cell-based macroscopic evacuation model. A network flow algorithm based on the sample average approximation approach is used as part of the solution procedure. Finally, a sample network is used to demonstrate the salient features of the proposed stochastic model and solution procedure.
KW - Endogenously determined risks
KW - Evacuation planning
KW - Network flow algorithm
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U2 - 10.1007/s11067-014-9241-y
DO - 10.1007/s11067-014-9241-y
M3 - Article
AN - SCOPUS:84946483908
SN - 1566-113X
VL - 15
SP - 677
EP - 696
JO - Networks and Spatial Economics
JF - Networks and Spatial Economics
IS - 3
ER -