O3-03-05: Evacuation planning to reduce resident stress for senior adult facilities

2015 ◽  
Vol 11 (7S_Part_5) ◽  
pp. P225-P225
Author(s):  
Sally Curtis
2007 ◽  
Vol 24 ◽  
pp. 223-232
Author(s):  
Noboru KIMATA ◽  
Shintaro TERANISHI ◽  
Toru FUTAGAMI

2014 ◽  
Vol 2 ◽  
pp. 486-494 ◽  
Author(s):  
Ismaila Abderhamane Ndiaye ◽  
Emmanuel Neron ◽  
Anais Linot ◽  
Nicolas Monmarche ◽  
Marc Goerigk

2018 ◽  
Vol 12 (3) ◽  
pp. 587-604
Author(s):  
Xiang Chen ◽  
Clayton Frazier ◽  
Rejina Manandhar ◽  
Zhigang Han ◽  
Peng Jia

Author(s):  
Joseph Kim ◽  
Tomoyuki Takabatake ◽  
Ioan NISTOR ◽  
Tomoya Shibayama

Soft measures such as evacuation planning are recommended to mitigate the loss of life during tsunamis. Two types of evacuation models are widely used: (1) Agent-based modelling (ABM) defines sets of rules that individual agents in a simulation follow during a simulated evacuation. (2) Geographical information systems (GIS) are more accessible to city planners, but cannot incorporate the dynamic behaviours found in ABMs. The two evacuation modelling methodologies were compared through a case study by assessing the state of evacuation preparedness and investigating potential mitigation options. The two models showed different magnitudes for mortality rates and facility demand but had similar trends. Both models agreed on the best solution to reduce the loss of life for the community. GIS may serve as a useful tool for initial investigation or as a validation tool for ABMs. ABMs are recommended for use when modelling evacuation until GIS methodologies are further developed.


2018 ◽  
Vol 52 (3) ◽  
pp. 779-805 ◽  
Author(s):  
Vedat Bayram ◽  
Hande Yaman

Shelter location and traffic allocation decisions are critical for an efficient evacuation plan. In this study, we propose a scenario-based two-stage stochastic evacuation planning model that optimally locates shelter sites and that assigns evacuees to nearest shelters and to shortest paths within a tolerance degree to minimize the expected total evacuation time. Our model considers the uncertainty in the evacuation demand and the disruption in the road network and shelter sites. We present a case study for a potential earthquake in Istanbul. We compare the performance of the stochastic programming solutions to solutions based on single scenarios and mean values.


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