Publications

Bandlow, Alisa B.; Jones, Katherine A.; Brown, Nathanael J.; Nozick, Linda K.

Abstract not provided.

Proceedings - Winter Simulation Conference

Brown, Nathanael J.; Jones, Katherine A.; Nozick, Linda K.; Xu, Ningxiong

The performance of a multi-layered security system, such as those protecting high-value facilities or critical infrastructures, is characterized using several different attributes including detection and interruption probabilities, costs, and false/nuisance alarm rates. The multitude of technology options, alternative locations and configurations for those technologies, threats to the system, and resource considerations that must be weighed make exhaustive evaluation of all possible architectures extremely difficult. This paper presents an optimization model and a computationally efficient solution procedure to identify an estimated frontier of system configuration options which represent the best design choices for the user when there is uncertainty in the response time of the security force, once an intrusion has been detected. A representative example is described.

Brown, Nathanael J.; Jones, Katherine A.; Nozick, Linda K.; Xu, Ningxiong X.

Abstract not provided.

Sandia journal manuscript; Not yet accepted for publication

Brown, Nathanael J.; Jones, Katherine A.; Nozick, Linda K.; Xu, Ningxiong X.

This paper focuses on optimizing the selection and configuration of detection technologies to protect a target of interest. The ability of an intruder to simply reach the target is assumed to be sufficient to consider the security system a failure. To address this problem, we develop a game theoretic model of the strategic interactions between the system owner and a knowledgeable intruder. A decomposition-based exact method is used to solve the resultant model.

Brown, Nathanael J.; Jones, Katherine A.; Bandlow, Alisa B.; Nozick, Linda K.; Adair, Kristin L.; Gearhart, Jared L.; Russell, John L.; Xu, Ningxiong X.

Abstract not provided.

Gearhart, Jared L.; Adair, Kristin L.; Bandlow, Alisa B.; Brown, Nathanael J.; Russell, John L.

Abstract not provided.

Brown, Nathanael J.

Abstract not provided.

Trujillo, Manuel M.; Allen, Matthew M.; Brown, Nathanael J.; Baldwin, George T.

Abstract not provided.

IEEE Transactions on Power Systems

Jones, Dean A.; Brown, Nathanael J.

Abstract not provided.

Brown, Nathanael J.; Gearhart, Jared L.; Jones, Dean A.

Abstract not provided.

International Journal of Critical Infrastructures

Vugrin, Eric D.; Brown, Nathanael J.

Abstract not provided.

Allen, Matthew M.; Brown, Nathanael J.; Trujillo, Manuel M.

Abstract not provided.

Brown, Nathanael J.; Gearhart, Jared L.; Jones, Dean A.

Abstract not provided.

Gearhart, Jared L.; Brown, Nathanael J.; Jones, Dean A.

Abstract not provided.

Gearhart, Jared L.; Brown, Nathanael J.

Abstract not provided.

Proposed for publication in Journal of Global Optimization.

Jones, Dean A.; Brown, Nathanael J.; Gearhart, Jared L.; Adair, Kristin L.

Abstract not provided.

Brown, Nathanael J.; Shirah, Donald N.; Turk, Adam L.

Abstract not provided.

Gearhart, Jared L.; Brown, Nathanael J.; Jones, Dean A.

Abstract not provided.

Social Networks

Jones, Dean A.; Brown, Nathanael J.

This paper presents an extension to generalized blockmodeling where there are more than two types of objects to be clustered based on valued network data. We use the ideas in homogeneity block modeling to develop an optimization model to perform the clustering of the objects and the resulting partitioning of the ties so as to minimize the inconsistency of an empirical block with an ideal block. The ideal block types used in this modeling are null, complete and a new type that is related to that developed in Ziberna (2007). Three case studies are presented, two based on the Southern Women dataset (Davis et al. 1941) and a third based on passenger air travel in the Continental United States.

Allen, Matthew M.; Brown, Nathanael J.

Abstract not provided.

Allen, Matthew M.; Weber, Thomas M.; Brown, Nathanael J.

Abstract not provided.

Brown, Nathanael J.; Gearhart, Jared L.; Jones, Dean A.

Abstract not provided.

Vugrin, Eric D.; Brown, Nathanael J.

Critical infrastructure resilience has become a national priority for the U. S. Department of Homeland Security. System resilience has been studied for several decades in many different disciplines, but no standards or unifying methods exist for critical infrastructure resilience analysis. This report documents the results of a late-start Laboratory Directed Research and Development (LDRD) project that investigated the identification of optimal recovery strategies that maximize resilience. To this goal, we formulate a bi-level optimization problem for infrastructure network models. In the 'inner' problem, we solve for network flows, and we use the 'outer' problem to identify the optimal recovery modes and sequences. We draw from the literature of multi-mode project scheduling problems to create an effective solution strategy for the resilience optimization model. We demonstrate the application of this approach to a set of network models, including a national railroad model and a supply chain for Army munitions production.