"This book provides readers with descriptions of security and defense-related decision and planning problems and solutions incorporating a broad array of contemporary OR techniques. In particular, this book addresses and features original research and reviews on (1) innovative applications of OR techniques and methodologies in defense and (2) relevant theoretical frameworks and the latest empirical research findings in the area"--
"This book explores problems which incorporate every aspect of contemporary quantitative applications of operations research methods in military. It address and feature original research on the innovative applications of techniques and methodologies on defense and military related problems and relevant theoretical frameworks and the latest empirical research findings in the area"--
AbstractThe allocation of underwater sensors for tracking, localization, and surveillance purposes is a fundamental problem in anti‐submarine warfare. Inexpensive passive receivers have been heavily utilized in recent years; however, modern submarines are increasingly quiet and difficult to detect with receivers alone. Recently, the idea of deploying noncollocated sources and receivers has emerged as a promising alternative to purely passive sensor fields and to traditional sonar fields composed of collocated sources and receivers. Such a multistatic sonar network carries a number of advantages, but it also brings increased system complexity resulting from its unusual coverage patterns. In this work, we study the problem of optimally positioning active multistatic sonar sources for a point coverage application where all receivers and points of interest are fixed and stationary. Using a definite range sensor model, we formulate exact methods and approximation algorithms for this problem and compare these algorithms via computational experiments. We also examine the performance of these algorithms on a discrete approximation of a continuous area coverage problem and find that they offer a significant improvement over two types of random sensor deployment.
The problem of determining effective allocation schemes of underwater sensors for surveillance, search, detection, and tracking purposes is a fundamental research area in military operations research. Among the various sensor types, multistatic sonobuoy systems are a promising development in submerged target detection systems. These systems consist of sources (active sensors) and receivers (passive sensors), which need not be collocated. A multistatic sonobuoy system consisting of a single source and receiver is called a bistatic system. The sensing zone of this fundamental system is defined by Cassini ovals. The unique properties and unusual geometrical profile of these ovals distinguish the bistatic sensor allocation problem from conventional sonar placement problems. This study is aimed at supporting decision makers in making the best use of bistatic sonobuoys to detect stationary and mobile targets transiting through an area of interest. We use integral geometry and geometric probability concepts to derive analytic expressions for the optimal source and receiver separation distances to maximize the detection probability of a submerged target. We corroborate our analytic results using Monte Carlo simulation. Our approach constitutes a valuable "back of the envelope" method for the important and difficult problem of analyzing bistatic sonar performance.
The article of record as published may be found at https://doi.org/10.1002/nav.21807 ; The problem of determining effective allocation schemes of underwater sensors for surveillance, search, detection, and tracking purposes is a fundamental research area in military operations research. Among the various sensor types, multistatic sonobuoy systems are a promising development in submerged target detection systems. These systems consist of sources (active sensors) and receivers (passive sensors), which need not be collocated. A multistatic sonobuoy system consisting of a single source and receiver is called a bistatic system. The sensing zone of this fundamental system is defined by Cassini ovals. The unique properties and unusual geometrical profile of these ovals distinguish the bistatic sensor allocation problem from conventional sonar placement problems. This study is aimed at supporting deci- sion makers in making the best use of bistatic sonobuoys to detect stationary and mobile targets transiting through an area of interest. We use integral geometry and geometric probability concepts to derive analytic expressions for the optimal source and receiver separation distances to maximize the detection probability of a submerged target. We corroborate our analytic results using Monte Carlo simulation. Our approach constitutes a valuable "back of the envelope" method for the important and difficult problem of analyzing bistatic sonar performance. ; Office of Naval Research ; Trkiye Bilimsel ve Teknolojik Aratirma Kurumu
The article of record as published may be found at http://dx.doi.org/10.1016/j.apenergy.2017.05.068 ; Hybrid microgrids that use renewable energy sources can improve energy security and islanding time while reducing costs. One potential beneficiary of these systems is the U.S. military, which can seek to improve energy security when operating in isolated areas by using a microgrid rather than relying on a fragile (or nonexistent) commercial network. Renewable energy sources can be intermittent and unpredictable, making it difficult to plan operations of a microgrid. We describe a scenario-robust mixedinteger linear program designed to utilize ensemble weather forecasts to improve the performance of a hybrid microgrid containing both renewable and traditional power sources. We exercise our model to quantify the benefit of using ensemble weather forecasts, and we predict the optimal performance of a hypothetical grid containing wind turbines by using simulated realistic weather forecast scenarios based on data. Because forecast quality degrades with lead time, we perform a sensitivity analysis to determine which planning horizon results in the best performance. Our results show that, for dayahead planning, longer planning horizons outperform shorter planning horizons in terms of cost of operations, but this improvement diminishes as the planning horizon lengthens. ; Office of Naval Research
The article of record as published may be found at http://dx.doi.org/10.1109/WSC.2014.7019964 ; Hybrid microgrids containing renewable energy sources represent a promising option for organizations wishing to reduce costs while increasing energy security and islanding time. A prime example of such an organization is the U.S. military, which often operates in isolated areas and whose reliance on a fragile commercial electric grid is seen as a security risk. However, incorporating renewable sources into a microgrid is difficult due to their typically intermittent and unpredictable nature. We use simulation techniques to investigate the performance of a hypothetical hybrid microgrid containing both wind turbines and fossil fuel based power sources. Our simulation model produces realistic weather forecast scenarios, which we use to exercise our optimization model and predict optimal grid performance. We perform a sensitivity analysis and find that for day-ahead planning, longer planning horizons are superior to shorter planning horizons, but this improvement diminishes as the length of the planning horizon increases.
