Operational Research Commons^™

Neural Extensions To Robust Parameter Design, Bernard Jacob Loeffelholz

Theses and Dissertations

Robust parameter design (RPD) is implemented in systems in which a user wants to minimize the variance of a system response caused by uncontrollable factors while obtaining a consistent and reliable system response over time. We propose the use of artificial neural networks to compensate for highly non-linear problems that quadratic regression fails to accurately model. RPD is conducted under the assumption that the relationship between system response and controllable and uncontrollable variables does not change over time. We propose a methodology to find a new set of settings that will be robust to moderate system degradation while remaining robust …

Uncertainty Quantification Of Multi-Component Isotope-Separation Cascade Model, Khoi D. Tran

Theses and Dissertations

Monte Carlo uncertainty quantification (UQ) capability has been added to a code for modeling multi-component steady-state isotope-separation enrichment cascades to characterize the propagation of uncertainties in input data that define the cascade and the feed. Random samples of error for every computational input are drawn from its individual uncertainty distribution and added to the inputs, creating a set of enrichment cascade problems with perturbed inputs. The set of problems is solved using the verified code. The cascade outputs are then characterized using the empirical cumulative distribution. The uncertainty output data are analyzed to gain new insights into the behaviors of …

Investigating An Optimal Decision Point For Probability Bounds Analysis Models When Used To Estimate Remedial Soil Volumes Under Uncertainty At Hazardous Waste Sites, Charles O. Dankwah

Walden Dissertations and Doctoral Studies

Hazardous waste site remediation cost estimation requires a good estimate of the contaminated soil volume. The United States Environmental Protection Agency (U.S. EPA) currently uses deterministic point values to estimate soil volumes but the literature suggests that probability bounds analysis (PBA) is the more accurate method to make estimates under uncertainty. The underlying statistical theory is that they are more accurate than deterministic estimates because probabilistic estimates account for data uncertainties. However, the literature does not address the problem of selecting an optimal decision point from the interval-valued PBA estimates. The purpose of this study was to identify the optimal …

Host-Based Multivariate Statistical Computer Operating Process Anomaly Intrusion Detection System (Paids), Glen R. Shilland

Theses and Dissertations

No abstract provided.

Multi-Objective Network Reliability Optimization Using Evolutionary Algorithms, Franciso Oswaldo Aguirre

Open Access Theses & Dissertations

This work presents a new multiple objective evolutionary algorithm to solve three well known network reliability allocation problems considering different conflicting objectives to be optimized simultaneously. The new algorithm is applied in the design of a telecommunication network that is formed for several stations or nodes interconnected by telecommunication links or paths. The problem presented in this work involves finding which links to activate in order to obtain connectivity in the nodes. The number of nodes that need to be connected depends of the case that is being evaluated. The three network reliability problems considered are: all-terminal, k-terminal, and two-terminal. …

A Confidence Paradigm For Classification Systems, Nathan J. Leap

Theses and Dissertations

There is no universally accepted methodology to determine how much confidence one should have in a classifier output. This research proposes a framework to determine the level of confidence in an indication from a classifier system where the output is or can be transformed into a posterior probability estimate. This is a theoretical framework that attempts to unite the viewpoints of the classification system developer (or engineer) and the classification system user (or war-fighter). The paradigm is based on the assumptions that the system confidence acts like, or can be modeled as a value and that indication confidence can be …

Improving Mixed Variable Optimization Of Computational And Model Parameters Using Multiple Surrogate Functions, David Bethea

Theses and Dissertations

This research focuses on reducing computational time in parameter optimization by using multiple surrogates and subprocess CPU times without compromising the quality of the results. This is motivated by applications that have objective functions with expensive computational times at high fidelity solutions. Applying, matching, and tuning optimization techniques at an algorithm level can reduce the time spent on unprofitable computations for parameter optimization. The objective is to recover known parameters of a flow property reference image by comparing to a template image that comes from a computational fluid dynamics simulation, followed by a numerical image registration and comparison process. Mixed …

Radical Impact Of Change In Actions And Confidence Index On Reverse Decision Making An Application Based Study, Swatee Trimbak Paithankar

Engineering Management & Systems Engineering Theses & Dissertations

While making decisions under uncertainty, people are often unaware of the logical approach to form the decision process. It is assumed that collecting details, analyzing and evaluating data is enough to make 'proper' decisions. However, past research in the decision making arena has significantly validated that there exists a class of decision problems which is complex, ill-structured and not defined to the level where decision makers can draw logical conclusions based on existing traditional decision approaches. RDM (reverse decision making), one of the novel approaches of decision making under conditions of uncertainty, has shown potential towards addressing some of these …

Choice And Optimization Of Forecasting Models For Container Port Throughput, Qingcheng Xue

World Maritime University Dissertations

No abstract provided.

The Study On The Empty Container Repositioning Of Container Leasing Company, Yi Zhao

World Maritime University Dissertations

No abstract provided.

Uncertainty Assessment In High-Risk Environments Using Probability, Evidence Theory And Expert Judgment Elicitation, Stella Barberis Bondi

Engineering Management & Systems Engineering Theses & Dissertations

The level of uncertainty in advanced system design is assessed by comparing the results of expert judgment elicitation to probability and evidence theory. This research shows how one type of monotone measure, namely Dempster-Shafer Theory of Evidence can expand the framework of uncertainty to provide decision makers a more robust solution space. The issues imbedded in this research are focused on how the relevant predictive uncertainty produced by similar action is measured.

This methodology uses the established approach from traditional probability theory and Dempster-Shafer evidence theory to combine two classes of uncertainty, aleatory and epistemic. Probability theory provides the mathematical …

A Multivariate Magnitude Robust Control Chart For Mean Shift Detection And Change Point Estimation, Ryan M. Harrell

Theses and Dissertations

Statistical control charts are often used to detect a change in an otherwise stable process. This process may contain several variables affecting process stability. The goal of any control chart is to detect an out-of-control state quickly and provide insight on when the process actually changed. This reduces the off-line time the quality engineer spends assigning causality. In this research, a multivariate magnitude robust chart (MMRC) was developed using a change point model and a likelihood-ratio approach. Here the process is considered in-control until one or more normally distributed process variables permanently and suddenly shifts to out-of-control, stable value. Using …

Improved Hyperspectral Image Testing Using Synthetic Imagery And Factorial Designed Experiments, Joseph P. Bellucci

Theses and Dissertations

The goal of any remote sensing system is to gather data about the geography it is imaging. In order to gain knowledge of the earth's landscape, post-processing algorithms are developed to extract information from the collected data. The algorithms can be intended to classify the various ground covers in a scene, identify specific targets of interest, or detect anomalies in an image. After the design of an algorithm comes the difficult task of testing and evaluating its performance. Traditionally, algorithms are tested using sets of extensively ground truthed test images. However, the lack of well characterized test data sets and …

Fisheries Research Contract Report No. 14 - Aquatic Animal Health Subprogram: Development Of A National Translocation Policy Using Abalone And Prawns As Templates For Other Aquatic Species (Frdc Project No. 2004/080) Final Report, Brian Jones, Fran Stephens

Fisheries Research Contract Reports

The use of scientifically based hazard identification, risk analysis and risk management is fundamental to managing unwanted effects. Hazards, such as quarantine incursions, will continue to occur despite the use of risk assessment methodologies but the frequency and severity of their occurrence will be reduced.

This was recognised by the Ministerial Council on Forestry, Fisheries and Aquaculture in 1999 when they published the "National policy for the translocation of live aquatic organisms".

This FRDC project provides a simple risk assessment methodology based on the Australian Standard for Risk Management (AS/NZS 4360: 2004) and one that is consistent with the Ministerial …

Optimization Of A Multi-Echelon Repair System Via Generalized Pattern Search With Ranking And Selection: A Computational Study, Derek D. Tharaldson

Theses and Dissertations

With increasing developments in computer technology and available software, simulation is becoming a widely used tool to model, analyze, and improve a real world system or process. However, simulation in itself is not an optimization approach. Common optimization procedures require either an explicit mathematical formulation or numerous function evaluations at improving iterative points. Mathematical formulation is generally impossible for problems where simulation is relevant, which are characteristically the types of problems that arise in practical applications. Further complicating matters is the variability in the simulation response which can cause problems in iterative techniques using the simulation model as a function …

A Dyadic Composition To Foster Virtual Team Effectiveness: An Experimental Study, Gamze Karayaz

Engineering Management & Systems Engineering Theses & Dissertations

The importance of effectiveness for virtual teamwork continues to gain momentum as technology and globalization of work accelerate. The implementation of virtual teams provides one approach to enhance competitiveness, overcoming the disadvantages of space and time differences through collaborative technologies. The influence of structure to virtual team performance has not been clearly established in the literature. The purpose of this research study was to investigate the effectiveness of a dyad structured approach for virtual teams using a quasi-experimental research design.

This research investigated four questions related to the influence of structure on virtual team effectiveness related to task performance, communication …

Optimal Sampling Of A Chemical Hazard Area, Jennifer R. Plourde

Theses and Dissertations

This thesis proposes a methodology for optimally sampling a chemical hazard area subsequent to a chemical weapons attack. The objective is to identify the maximum number of areas that no longer require protective gear for safe operations. We model the area as an undirected graph and employ network analysis techniques to provide a methodological framework for identifying an optimal sampling sequence within a fixed time limit. We propose four models that characterize the secondary vapor concentrations: i) static and deterministic, ii) static and stochastic, iii) dynamic and deterministic, and iv) dynamic and stochastic. Comparisons of the static cases and their …

Lean Energy Analysis: Identifying, Discovering And Tracking Energy Savings Potential, J. Kelly Kissock, John Seryak

Mechanical and Aerospace Engineering Faculty Publications

Energy in manufacturing facilities is used for direct production of goods, space conditioning, and general facility support such as lighting. This paper presents a methodology, called lean energy analysis, LEA, for graphically and statistically analyzing plant energy use in terms of these major end uses.

The LEA methodology uses as few as 60 easily obtainable data points. Multivariable change-point models of electricity and natural gas use as functions of outdoor air temperature and production data are developed. The statistical models are used to subdivide plant energy use into facility, space-conditioning and production-related components.

These breakdowns suggest the savings potential from …

Development Of A Systems Engineering Model Of The Chemical Separations Process, Yitung Chen, Sean Hsieh

Separations Campaign (TRP)

The whole chemical separation process is complex to the point that definitely requires certain level of systematic coordination. To perform smoothly and meet the target extraction rates among those processes, this research proposed a general-purpose systems engineering model.

A general purposed systems engineering model, Transmutation Research Program System Engineering Model Project (TRPSEMPro), was developed based on the above design concept. The system model includes four main parts: System Manager, Model Integration, Study Plan, and Solution Viewer. System Manager supervises all the case (problem) creation, and functionality definition. Model Integration identifies chemical extraction processes and their execution sequence. Study Plan is …

Agent Based Simulation Seas Evaluation Of Dodaf Architecture, Gregory V. Destefano

Theses and Dissertations

With Department of Defense (DoD) weapon systems being deeply rooted in the command, control, communications, computers, intelligence, surveillance, and reconnaissance (C4ISR) structure, it is necessary for combat models to capture C4ISR effects in order to properly assess military worth. Unlike many DoD legacy combat models, the agent based model System Effectiveness and Analysis Simulation (SEAS) is identified as having C4ISR analysis capabilities. In lieu of requirements for all new DoD C4ISR weapon systems to be placed within a DoD Architectural Framework (DoDAF), investigation of means to export data from the Framework to the combat model SEAS began. Through operational, system, …

An Investigation Of The Effects Of Correlation, Autocorrelation, And Sample Size In Classifier Fusion, Nathan J. Leap

Theses and Dissertations

This thesis extends the research found in Storm, Bauer, and Oxley, 2003. Data correlation effects and sample size effects on three classifier fusion techniques and one data fusion technique were investigated. Identification System Operating Characteristic Fusion (Haspert, 2000), the Receiver Operating Characteristic Within Fusion method (Oxley and Bauer, 2002), and a Probabilistic Neural Network were the three classifier fusion techniques; a Generalized Regression Neural Network was the data fusion technique. Correlation was injected into the data set both within a feature set (autocorrelation) and across feature sets for a variety of classification problems, and sample size was varied throughout. Total …

Object-Oriented Architecture For Concurrent Processes In A Port Simulation, Reejo Mathew

Electrical & Computer Engineering Theses & Dissertations

An architectural model to represent the resources and infrastructure within a cargo terminal, as well as to support the concurrent but opposite flow of cargo within the terminal, is presented in this thesis. The model supports the configuration of an individual cargo terminal according to its characteristics, as well as the processing involved in the simultaneous flow of cargo in opposite directions through the terminal. This is useful in the analysis of the flow of military cargo and aids the decision-making process to increase the efficiency and throughput of any military operation. This model has been developed with the aim …

Identifying Enlisted Stay And Leave Population Characteristics With Discriminant Analysis, Zabrina Y. Hoggard

Theses and Dissertations

The research contribution of this thesis is the first known integrated architecture and feature selection algorithm for Radial Basis Neural Networks (RBNNs). The objective is to apply the network iteratively to determine the final architecture and feature set used to evaluate a problem. Additionally, this thesis compares three different classification techniques, Discriminant Analysis (DA), Feed-Forward Neural Networks (FFN) and RBNNs against several hard to solve problems. These problems were used to evaluate general classifier performance as well as the performance of the feature selection techniques. This thesis describes the classification techniques as well as the measures used to evaluate them. …

Selecting Salient Features In High Feature To Exemplar Ratio Conditions, Ismail Aslan

Theses and Dissertations

A key tenet to the Air Force's vision of Global Vigilance, Reach, and Power is the ability to project power via the use of aerial refueling. Scheduling of limited tanker resources is a major concern for Air Mobility Command (AMC). Currently the Combined Mating and Ranging Planning System (CMARPS) is used to plan aerial refueling operations, however due to the complex nature of the program and the length of time needed to run a scenario, the need for a simple tool that runs in much shorter time is desired. Ant colony algorithms are recently developed heuristics for finding solutions to …

An Integrated Architecture And Feature Selection Algorithm For Radial Basis Neural Networks, Timothy D. Flietstra

Theses and Dissertations

There are two basic ways to control an Unmanned Combat Aerial Vehicle (UCAV) as it searches for targets: allow the UCAV to act autonomously or employ man-in-the-loop control. There are also two target sets of interest: fixed or mobile targets. This research focuses on UCAV-based targeting of mobile targets using man-in-the-loop control. In particular, the interest is in how levels of satellite signal latency or signal degradation affect the ability to accurately track, target, and attack mobile targets. This research establishes a weapon effectiveness model assessing targeting inaccuracies as a function of signal latency and/or signal degradation. The research involved …

Modeling And Analysis Of Multicommodity Network Flows Via Goal Programming, Matthew A. Scott

Theses and Dissertations

In this research we focused on the mobility system modeled by the AMC mobility planner's calculator (AMPCALC). We developed AMPCALC as a user-friendly tool and allow the user to easily carry out strategic airlift, air refueling and aeromedical evacuation calculations that are covered in Air Force Pamphlet 10-1403. In this study, Excel software and its macro language, Visual Basic for Application, are our two main tools. In the methodology of the thesis we examined fundamental aspects of the mobility system in AMPCALC. We discussed formulation logic of the mobility cycle. We presented ramp use optimization and tanker optimization processes. We …

Modeling Information Assurance, Joseph E. Beauregard

Theses and Dissertations

The ever-increasing speed of information systems allows decision-makers around the world to gather, process, and disseminate information almost instantaneously. However, with this benefit there comes a price. Information is valuable and therefore a target to those who do not have it or wish to destroy it. The Internet has allowed information to flow freely, but it has also made information vulnerable to many forms of corruption. The U. S. military controls much of the world's most sensitive information, and since it cannot sacrifice losing the speed at which this information is currently processed and disseminated, it must find a way …

A Process For Vectoring Offensive Information Warfare As A Primary Weapon Option Within The United States Air Force, Sheila G. Bennett

Theses and Dissertations

Consistently and comprehensively using Information Operations (IO) capabilities as primary weapon option within the Air Force is the next step to operationalizing IO within the Air Force. Doctrine and official guidance has set the variables of mission and concepts of operations, organizational structure, and IW players in place. The missing variable to operationalizing IO and probably the most difficult is the 'how' or process of the equation. This research will introduce a useable process that can be incorporated within the Air Force for integrating offensive IW activities into the current and given environment. The process is the basis for further …

Malicious Hackers: A Framework For Analysis And Case Study, Laura J. Kleen

Theses and Dissertations

Recent years have seen an increase in the number and severity of Information Operations (IO) attacks upon DoD resources. At a higher level, the US as a whole has come under cyber attack by individuals and groups seeking thrills, monetary gain, publicity for their causes, and myriad other goals. This effort develops a first cut model of individual hacker mentality that can be utilized to improve threat assessment, mitigate Information Assurance (IA) vulnerabilities, and improve risk assessment. Further, it is a first step toward automated characterization of Information Warfare (IW) attacks based upon hacker types. All hackers are not the …

Minimum Distance Estimation For Time Series Analysis With Little Data, Hakan Tekin

Theses and Dissertations

Minimum distance estimate is a statistical parameter estimate technique that selects model parameters that minimize a good-of-fit statistic. Minimum distance estimation has been demonstrated better standard approaches, including maximum likelihood estimators and least squares, in estimating statistical distribution parameters with very small data sets. This research applies minimum distance estimation to the task of making time series predictions with very few historical observations. In a Monte Carlo analysis, we test a variety of distance measures and report the results based on many different criteria. Our analysis tests the robustness of the approach by testing its ability to make predictions when …