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MOR Journal Abstracts
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Proposed
Network Centric Warfare Metrics: From Connectivity to the OODA Cycle (Michael
F. Ling, Terry Moon and Ed Kruzins)
The
Bang-Soak Theory of Missile Attack and Terminal Defense (Alan
Washburn)
This
paper describes a spreadsheet-level model for analyzing attacks by a small,
mixed collection of ICBMs, perhaps including decoys, on a set of targets
individually defended by terminal ABMs. The central questions are how a fixed
supply of ABMs should be divided up among the targets, and the resulting
effectiveness of the optimized defense. All ABMs are assumed perfect in the sense that each ABM
eliminates the reentry vehicle at which it is aimed.
Since the ABM assignments are apparent to the attacker, he can “soak
them up” by presenting the appropriate number of his least effective reentry
vehicles to the subject target. The
target is then vulnerable to any remaining “bangs” among the attackers. (Pg.
15)
Planning
Dissimilar Paths for Military Units (Karthik Thyagarajan, Rajan Batta, Mark H. Karwan and
Robert J. Szczerba)
Evaluation
of Mobilization and Deployment Plan of an Armored Battalion (Selim Müslüm and
İhsan
Sabuncuoğlu)
Being ready for war as soon as possible and with minimum casualties during the crises is the first mission of the troops. Mobilization and deployment plans arise as the most important tools for Army as they cover all the activities that troops must execute to respond against enemy immediately. In this paper, we study the performance of the mobilization and deployment plans of a Turkish armored battalion via simulation. The proposed simulation model is developed for military operation planners to analyse mobilization and deployment operation of troops early in decision process; perform bottleneck analysis and take necessary actions for the main problem areas. The proposed model can also reduce the risk of military operations before conducting them in actual war conditions. Moreover, it is used to identify the significant factors of enemy threat, detect the most hazardous region and the most hazardous factor for each region, and discover the system boundaries. The simulation model is developed using ARENA simulation system. The output of the model is analysed by the experimental design and ranking/selection procedures. A related bibliography is also provided in the paper. (Pg. 43)
Input-Output
Modeling for Assessing Cascading Effects (Mark A. Gallagher, Anthony W.
Snodgrass and Gregory J. Ehlers)
Mission
Oriented Risk and Design Analysis of Critical Information Systems (Donald
L. Buckshaw, Gregory S. Parnell,
FS, Willard L. Unkenholz, Donald L. Parks, James M. Wallner and O. Sami
Saydjari)
Information assurance is critical to future military operations. This paper describes a value-based information assurance methodology for Mission Oriented Risk and Design Analysis (MORDA) of critical information systems. The MORDA methodology was has been successfully applied on seven major Department of Defense risk assessment studies. MORDA is a quantitative risk assessment and risk management process that uses risk analysis techniques, multiple objective decision analysis models, and portfolio analysis techniques to evaluate information system designs. The process helps identify best allocation of system design and operation resources that will ensure an operable information system in a hostile and malicious operating environment. (Pg. 19)
Critical
Chain Project Scheduling for C-130 Aircraft Isochronal Inspection (Stephen M.
Swartz and Daniel D. Mattioda)
Input
Feature Selection For Automatic Target Recognition of Temporal Data (Trevor
I. Laine and Kenneth W.
Bauer)
Prior to engaging hostile targets, USAF doctrine requires a high level of confidence to “label” each target correctly. To increase “label” accuracy, combat identification may fuse data from multiple sensors through time. Automatic target recognition (ATR) algorithms may then be required to fuse sensor data that is highly correlated. The authors suggest the use of a “one big net” neural network model to fuse all sensor information. To improve classification accuracy state-of-the art feature selection methods are compared for a temporal neural network. A reduced set of input features is then observed to reduce classification accuracy variance while retaining the mean classification performance. (Pg. 51)
Using
Neural Networks for Estimating Cruise Missile Reliability (Maj Donald
Hoffman, Prof. Kenneth W. Bauer and Major Stephen P. Chambal)
In an effort to assist Air Combat Command (ACC) in its efforts to improve its current methodology for predicting the reliability of its Air Launched Cruise Missile (ALCM) and Advanced Cruise Missile (ACM) stockpiles; an easy to use and maintain model was developed. The requirements were a model that delivers a 24-month prediction of cruise missile reliability using existing data sources, collection methods and software. It should be easily maintainable and developed to allow a layperson to enter updated data and receive an accurate reliability prediction. Such a model is presented which allows for the fusion of logistics regression, feed-forward neural networks and radial basis function neural network models. (Pg. 5)
Ship
Repair Workflow Cost Model (Michael
E. McDevitt, Michael W. Zabarouskas and John C. Crook)
Refinement of Estimates: Using Logistic and Multiple Regression to Predict Cost Growth (Prof Edward D. White III and Maj John Bielecki)
Assessing cost growth for major Department of Defense weapon systems can be a difficult task to accomplish. Although experience and subjective reasoning has its place, incorporating statistical analysis in this assessment is a valuable tool to consider. Not only are empirical data and historical trends important for statistical analysis, so is the methodology chosen. In this study, the authors highlight a two-step regression procedure for predicting the likelihood and expected percentage increase of cost growth. Using this methodology, they produce statistically significant models highlighting the viability of ordinary least squares regression in conjunction with logistic regression for cost analysts to consider and to adopt for future uses. (Pg. 45)
Military
Operations Research Society (MORS) Oral History Project Interview of E.B.
Vandiver, III, FS (Michael Garrambone and Dr. Robert S. Sheldon, FS)
Equipping
Army Distribution Organizations Based On Modeling And Simulation (LTC Gregory
H. Graves)
The
U.S. Army Combined Arms Support Command (CASCOM) has developed an improved
methodology to determine container and material handling equipment (CMHE)
requirements to support theater distribution doctrine and the Army
transformation. LTC Greg Graves shows how spreadsheet models and simulation are
used together to determine the type and quantity of CMHE required for a unit to
achieve a designated level of throughput. Sensitivity analysis shows the change
in the level of performance caused by deviating from the baseline requirement.
This methodology is being used by combat developers at CASCOM to evaluate
and improve equipment levels for current and future organizations. (Pg. 5)
Analysis
and Visualisation of Surveillance Coverage by Scan Mapping (Patrick Hew)
This
paper introduces scan mapping for
analysing and visualising surveillance coverage, a technique that provides
insight into the collective performance of a surveillance force against a region
of responsibility over time. The technique departs from existing methods by its
study of operations as conducted, rather than of abstract predictions, and for
its study of quality of coverage as distinct from target detection and response.
Scan
mapping is built on the modelling of surveillance assets through swaths,
geographic regions monitored over intervals of time. The swaths are projected in
space to generate a scan history, from
which dwell, revisit,
and latency can be derived. These constructs are amenable to both
quantitative, statistical analysis and qualitative, map-based visualisation. The
underlying swath modelling factors out the technological details of individual
surveillance assets, and brings out the way that multiple assets complement each
other. The outputs can be compared with benchmarks for reporting on
effectiveness, can be used to guide the design of operations, and can provide
the baseline for correction of observations.
The
Defence Science and Technology Organisation has used scan mapping in operations
analysis support to Australia’s Northern Command, has suggested it for support
to decision-making on equipment acquisition, and has proposed it for integration
into Australia’s Joint Command Support System to boost situation awareness.
Scan mapping is software intensive and requires good operational data, and thus
draws on ongoing advances in scientific software and Knowledge Management. (Pg.
17)
A
Stochastic Salvo Model Analysis of the Battle of the Coral Sea (Michael J.
Armstrong and Michael B. Powell)
Historians
and "armchair admirals" are fond of speculating about how military
leaders might have altered history if they had made just one decision
differently. Michael Armstrong and
Michael Powell provide a more quantitative approach to such speculation for the
1942 carrier battle that saved Port Moresby from Japanese invasion.
They consider “what-if” questions such as: What if one more USN
aircraft carrier had been sent south to the Coral Sea, instead of west to the
Doolittle raid on Tokyo? They do
this by combining historical data with a recently developed stochastic model for
salvo combat. (Pg. 27)
Military
Operations Research Society (MORS) Oral History Project Interview of Saul I.
Gass (Gene Visco, FS and Bob Sheldon, FS)
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