Pandemic Influenza simulation based on Genetic Algorithm and Agent Based Modeling

2011 ◽  
Author(s):  
Ria Lestari ◽  
Adi Pancoro ◽  
Adang Suwandi Ahmad ◽  
Afwarman Manaf ◽  
Munawar Ahmad ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Pandemic Influenza ◽  
Agent Based Modeling ◽  
Agent Based ◽  
Simulation Based

scholarly journals Simulation-Based and Risk-Informed Assessment of the Effectiveness of Tsunami Evacuation Routes Using Agent-Based Modeling: A Case Study of Seaside, Oregon

2021 ◽  
Author(s):  
Zhenqiang Wang ◽  
Gaofeng Jia
Keyword(s):  
Transportation Network ◽  
Agent Based Modeling ◽  
Assessment Framework ◽  
Evacuation Simulation ◽  
Agent Based ◽  
Simulation Based ◽  
Evacuation Risk ◽  
Evacuation Routes ◽  
Evacuation Route

AbstractTypically, tsunami evacuation routes are marked using signs in the transportation network and the evacuation map is made to educate people on how to follow the evacuation route. However, tsunami evacuation routes are usually identified without the support of evacuation simulation, and the route effectiveness in the reduction of evacuation risk is typically unknown quantitatively. This study proposes a simulation-based and risk-informed framework for quantitative evaluation of the effectiveness of evacuation routes in reducing evacuation risk. An agent-based model is used to simulate the tsunami evacuation, which is then used in a simulation-based risk assessment framework to evaluate the evacuation risk. The route effectiveness in reducing the evacuation risk is evaluated by investigating how the evacuation risk varies with the proportion of the evacuees that use the evacuation route. The impacts of critical risk factors such as evacuation mode (for example, on foot or by car) and population size and distribution on the route effectiveness are also investigated. The evacuation risks under different cases are efficiently calculated using the augmented sample-based approach. The proposed approach is applied to the risk-informed evaluation of the route effectiveness for tsunami evacuation in Seaside, Oregon. The evaluation results show that the route usage is overall effective in reducing the evacuation risk in the study area. The results can be used for evacuation preparedness education and hence effective evacuation.

Simulation-based analyses of an evacuation from a metropolis during a bombardment

SIMULATION ◽  
2014 ◽  
Vol 90 (11) ◽  
pp. 1244-1267 ◽  
Author(s):  
Jang Won Bae ◽  
SeHoon Lee ◽  
Jeong Hee Hong ◽  
Il-Chul Moon
Keyword(s):  
Initial Conditions ◽  
Real Data ◽  
Agent Based Modeling ◽  
Agent Based Model ◽  
Target Region ◽  
Agent Based ◽  
Virtual Experiments ◽  
The Road ◽  
Simulation Based ◽  
The Military

The bombardment of a metropolis is considered a nightmare scenario. To reduce losses from such an assault, big cities have developed evacuation policies in case of bombardment. However, to build efficient evacuation policies, much footing data is required that considers both military and civilian views. Agent-based modeling and simulation could be utilized as a method to obtain the footing data. In this paper, we develop an evacuation agent-based model that describes a massive evacuation through the road network of a metropolis during a bombardment. In particular, our model took account of bombing strategies (i.e. the military view) as well as the characteristics of roads and evacuation agents (i.e. the civilian view) in order to analyze evacuations from both military and civilian perspectives. Moreover, we applied real data from a target region to calibrate parameters and initial conditions of the evacuation agent-based models, which increased the reliability of simulation results. Using the evacuation agent-based model, we designed and performed virtual experiments with varying military and civilian factors. Through the various analyses on the experiment results, we showed that our model could be a framework that provides footing data to develop efficient evacuation policies and preparations.

scholarly journals An Agent-Based Modeling for Pandemic Influenza in Egypt

2012 ◽  
pp. 205-218 ◽  
Author(s):  
Khaled M. Khalil ◽  
M. Abdel-Aziz ◽  
Taymour T. Nazmy ◽  
Abdel-Badeeh M. Salem
Keyword(s):  
Pandemic Influenza ◽  
Agent Based Modeling ◽  
Agent Based

Simulation-based optimization of radiotherapy: Agent-based modeling and reinforcement learning

2017 ◽  
Vol 133 ◽  
pp. 235-248 ◽  
Author(s):  
Ammar Jalalimanesh ◽  
Hamidreza Shahabi Haghighi ◽  
Abbas Ahmadi ◽  
Madjid Soltani
Keyword(s):  
Reinforcement Learning ◽  
Agent Based Modeling ◽  
Agent Based ◽  
Simulation Based ◽  
Simulation Based Optimization
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