Naval Postgraduate School

About: Naval Postgraduate School is a education organization based out in Monterey, California, United States. It is known for research contribution in the topics: Tropical cyclone & Nonlinear system. The organization has 5246 authors who have published 11614 publications receiving 298300 citations. The organization is also known as: NPS & U.S. Naval Postgraduate School.

Comparing syndromic surveillance detection methods: EARS' versus a CUSUM-based methodology.

Abstract: SUMMARY This paper compares the performance of three detection methods, entitled C1, C2, and C3, that are implemented in the early aberration reporting system (EARS) and other syndromic surveillance systems versus the CUSUM applied to model-based prediction errors. The cumulative sum (CUSUM) performed significantly better than the EARS’ methods across all of the scenarios we evaluated. These scenarios consisted of various combinations of large and small background disease incidence rates, seasonal cycles from large to small (as well as no cycle), daily effects, and various types and levels of random daily variation. This leads us to recommend replacing the C1, C2, and C3 methods in existing syndromic surveillance systems with an appropriately implemented CUSUM method. Published in 2008 by John Wiley & Sons, Ltd.

Dantzig-Wolfe Decomposition for Solving Multistage Stochastic Capacity-Planning Problems

Abstract: We describe a multistage, stochastic, mixed-integer programming model for planning capacity expansion of production facilities. A scenario tree represents uncertainty in the model; a general mixed-integer program defines the operational submodel at each scenario-tree node, and capacity-expansion decisions link the stages. We apply “variable splitting” to two model variants, and solve those variants using Dantzig-Wolfe decomposition. The Dantzig-Wolfe master problem can have a much stronger linear programming relaxation than is possible without variable splitting, over 700% stronger in one case. The master problem solves easily and tends to yield integer solutions, obviating the need for a full branch-and-price solution procedure. For each scenario-tree node, the decomposition defines a subproblem that may be viewed as a single-period, deterministic, capacity-planning problem. An effective solution procedure results as long as the subproblems solve efficiently, and the procedure incorporates a good “duals stabilization method.” We present computational results for a model to plan the capacity expansion of an electricity distribution network in New Zealand, given uncertain future demand. The largest problem we solve to optimality has six stages and 243 scenarios, and corresponds to a deterministic equivalent with a quarter of a million binary variables.

Optimizing Ship Berthing

Abstract: : Ship berthing plans reserve a location for inbound U.S. Navy surface vessels prior to their port entrance, or reassign ships once in port to allow them to complete, in a timely manner, reprovisioning, repair, maintenance, training, and certification tests prior to redeploying for future operational commitments. Each ship requires different services when in port, such as shore power, crane, ordnance, and fuel. Unfortunately, not all services are offered at all piers, and berth shifting is disruptive and expensive: A port operations scheduler strives to reduce unnecessary berth shifts. We present an optimization model for berth planning and demonstrate it for Norfolk Naval Station, which exhibits all the richness of berthing problem:. the Navy faces.