Spatial and objective decompositions for very large SCAPs
CPAIOR'11 Proceedings of the 8th international conference on Integration of AI and OR techniques in constraint programming for combinatorial optimization problems
Strategic planning for disaster recovery with stochastic last mile distribution
CPAIOR'10 Proceedings of the 7th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Computational disaster management
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Humanitarian/emergency logistics models: a state of the art overview
Proceedings of the 2013 Summer Computer Simulation Conference
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Each year, about 500 natural disasters kill approximately 70,000 people and affect more than 200 million people worldwide. In the aftermath of such events, large quantities of supplies are needed to provide relief aid to the affected. CARE International is one of the largest humanitarian organizations that provide relief aid to disaster survivors. The most vital issues in disaster response are agility in mobilizing supplies and effectiveness in distributing them. To improve disaster response, a research group from Georgia Institute of Technology collaborated with CARE to develop a model to evaluate the effect that pre-positioning relief items would have on CARE's average relief-aid emergency response time. The model's results helped CARE managers to determine a desired configuration for the organization's pre-positioning network. Based on the results of our study and other factors, CARE has pre-positioned relief supplies in three facilities around the world.