Hurricanes can severely damage the electric power system, and therefore, predicting the potential impact of an approaching hurricane is of importance for facilitating planning and storm-response activities. A data mining approach, classification and regression trees (CART), was employed to...

Accurate estimates of the duration of power outages caused by hurricanes prior to landfall are valuable for utility companies and government agencies that wish to plan and optimize their restoration efforts. Accurate pre-storm estimates are also important information for customers and operators...

<Para ID="Par1">The links between climate change and tropical cyclone behavior are frequently studied but still uncertain. This uncertainty makes planning for climate change a difficult task. Here we focus on one area of climate-related risk: the impact of tropical cyclones on United States power systems, and...</para>

An effective emergency medical service (EMS) response to emergency medical calls during extreme weather events is a critical public service. Nearly all models for allocating EMS resources focus on normal operating conditions. However, public health risks become even more critical during extreme...

The application of stochastic heuristic, like tabu search or simulated annealing, to address hard discrete optimization problems has been an important advance for efficiently obtaining good solutions in a reasonable amount of computing time. A challenge when applying such heuristics is assessing...

To mitigate the threat of nuclear terrorism within the US using nuclear material that has been smuggled into the country, the US Bureau of Customs and Border Protection has expanded its cargo container detection capabilities at ports of entry into the US This paper formulates a risk-based...

This paper focuses on detecting nuclear weapons on cargo containers using port security screening methods, where the nuclear weapons would presumably be used to attack a target within the United States. This paper provides a linear programming model that simultaneously identifies optimal primary...

Risk classification refers to the use of observable characteristics by insurers to group individuals with similar expected claims, to compute the corresponding premiums, and thereby to reduce asymmetric information. Permitting risk classification may reduce informational asymmetry-induced...

Risk classification refers to the use of observable characteristics by insurers to group individuals with similar expected claims, compute the corresponding premiums, and thereby reduce asymmetric information. An efficient risk classification system generates premiums that fully reflect the...

We study adverse selection using data from an 1808 Act of British Parliament that effectively opened a market for life annuities. Our analysis indicates significant selection effects. The evidence for adverse selection is strongest for a sub-sample of annuitants whose annuities were purchased by...