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Articles 91 - 120 of 609
Full-Text Articles in Operational Research
Air Force Specialty Code Assignment Optimization, Rebecca L. Reynolds
Air Force Specialty Code Assignment Optimization, Rebecca L. Reynolds
Theses and Dissertations
Each year, the Air Force Personnel Center determines which career field newly commissioned officers will serve under during their time in the Air Force. The career fields are assigned while considering five priorities, dictated by Headquarters Air Force, Manpower and Personnel: target number of cadets, education requirements, average cadet percentile, cadet source of commissioning, and cadet preference. A mixed-integer linear program with elasticized constraints is developed to generate cadet assignments according to these priorities. Each elasticized constraint carries an associated reward and penalty, which is used to dictate the importance of the constraint within the model. A subsequent analysis is …
Inverse Optimization: Inferring Unknown Instance Parameters From Observed Decisions, Keith Batista
Inverse Optimization: Inferring Unknown Instance Parameters From Observed Decisions, Keith Batista
Theses and Dissertations
The objective of this research is to develop procedures that estimate selected, unknown parameters over an adversary's investment portfolio across a set of new or existing technologies. To solve for the selected unknown parameters, it is assumed that the adversary is maximizing the portfolio optimization problem and investing along the efficient frontier. The first technique is when an unknown risk attitude exists but all other parameters were known (i.e. expected return, variance, covariance). An adaptive line search technique that iteratively solved the portfolio optimization problem until the adversary's risk parameter was found. The second problem that was solved was when …
Approximate Dynamic Programming For An Unmanned Aerial Vehicle Routing Problem With Obstacles And Stochastic Target Arrivals, Kassie M. Gurnell
Approximate Dynamic Programming For An Unmanned Aerial Vehicle Routing Problem With Obstacles And Stochastic Target Arrivals, Kassie M. Gurnell
Theses and Dissertations
The United States Air Force is investing in artificial intelligence (AI) to speed analysis in efforts to modernize the use of autonomous unmanned combat aerial vehicles (AUCAVs) in strike coordination and reconnaissance (SCAR) missions. This research examines an AUCAVs ability to execute target strikes and provide reconnaissance in a SCAR mission. An orienteering problem is formulated as anMarkov decision process (MDP) model wherein a single AUCAV must optimize its target route to aid in eliminating time-sensitive targets and collect imagery of requested named areas of interest while evading surface-to-air missile (SAM) battery threats imposed as obstacles. The AUCAV adjusts its …
Comparison Of Lightning Warning Radii Distributions, Michael M. Maestas
Comparison Of Lightning Warning Radii Distributions, Michael M. Maestas
Theses and Dissertations
Previous research investigating lightning warning radii about the Cape Canaveral space launch facilities have focused on reducing these radii from either 5 nautical miles (NM) to 4 NM or from 6 NM to 5 NM depending on the structures being protected. Some of these findings have suggested the possibility of both a seasonal difference (warm versus cold) and lightning detection events (cloud-to-ground lightning (CG) or total lightning (TL)) impacting these radii and associated risk levels. Utilizing the 2017-2020 data provided by the 45th Weather Squadron at Patrick Space Force Base via the Mesoscale Eastern Range Lightning Information System (MERLIN), this …
Multiagent Routing Problem With Dynamic Target Arrivals Solved Via Approximate Dynamic Programming, Andrew E. Mogan
Multiagent Routing Problem With Dynamic Target Arrivals Solved Via Approximate Dynamic Programming, Andrew E. Mogan
Theses and Dissertations
This research formulates and solves the multiagent routing problem with dynamic target arrivals (MRP-DTA), a stochastic system wherein a team of autonomous unmanned aerial vehicles (AUAVs) executes a strike coordination and reconnaissance (SCAR) mission against a notional adversary. Dynamic target arrivals that occur during the mission present the team of AUAVs with a sequential decision-making process which we model via a Markov Decision Process (MDP). To combat the curse of dimensionality, we construct and implement a hybrid approximate dynamic programming (ADP) algorithmic framework that employs a parametric cost function approximation (CFA) which augments a direct lookahead (DLA) model via a …
An Exploratory Analysis Of Time Series Econometric Data For Retention Forecasting Using Deep Learning, John C. O'Donnell
An Exploratory Analysis Of Time Series Econometric Data For Retention Forecasting Using Deep Learning, John C. O'Donnell
Theses and Dissertations
Officer retention in the Air Force has been researched many times in an attempt to better predict the personnel needs of the Air Force for the future. There has been previous work done in regards to specific AFSCs and how their retention compares to specific yet similar private sector jobs. This study considers different econometric time series statistics as a feature space and an average Air Force officer separation rate as the response variable for the multivariate time series analysis deep learning techniques. The econometric indicators used in this study are New Business Formations, New Durable Good Orders, and the …
Assessing The United States Foreign Assistance Activities Impact On Violent Conflicts, Daniel F. Feze
Assessing The United States Foreign Assistance Activities Impact On Violent Conflicts, Daniel F. Feze
Theses and Dissertations
The Global Fragility Act, H.R.2116 116th Cong. (2019), “directs the Department of State to establish the interagency Global Fragility Initiative to stabilize conflict-affected areas and prevent violence globally, and establishes funds to support such efforts”. The United States Agency for International Development (USAID) has identified deteriorating economies, weak or illegitimate political institutions, and competition over natural resources as causes of violence, extremism and instability (USAID, 2021). The agency gives priority to mitigating the causes and consequences of violent conflicts, instability and extremism and funds programs and activities to accomplish that (USAID, 2021). With this study, we aim to quantitatively assess …
Bayesian Convolutional Neural Network With Prediction Smoothing And Adversarial Class Thresholds, Noah M. Miller
Bayesian Convolutional Neural Network With Prediction Smoothing And Adversarial Class Thresholds, Noah M. Miller
Theses and Dissertations
Using convolutional neural networks (CNNs) for image classification for each frame in a video is a very common technique. Unfortunately, CNNs are very brittle and have a tendency to be over confident in their predictions. This can lead to what we will refer to as “flickering,” which is when the predictions between frames jump back and forth between classes. In this paper, new methods are proposed to combat these shortcomings. This paper utilizes a Bayesian CNN which allows for a distribution of outputs on each data point instead of just a point estimate. These distributions are then smoothed over multiple …
Team Air Combat Using Model-Based Reinforcement Learning, David A. Mottice
Team Air Combat Using Model-Based Reinforcement Learning, David A. Mottice
Theses and Dissertations
We formulate the first generalized air combat maneuvering problem (ACMP), called the MvN ACMP, wherein M friendly AUCAVs engage against N enemy AUCAVs, developing a Markov decision process (MDP) model to control the team of M Blue AUCAVs. The MDP model leverages a 5-degree-of-freedom aircraft state transition model and formulates a directed energy weapon capability. Instead, a model-based reinforcement learning approach is adopted wherein an approximate policy iteration algorithmic strategy is implemented to attain high-quality approximate policies relative to a high performing benchmark policy. The ADP algorithm utilizes a multi-layer neural network for the value function approximation regression mechanism. One-versus-one …
A Decision Analysis Framework To Consider Space Congestion In Orbit Selection, Anthony J. Correale
A Decision Analysis Framework To Consider Space Congestion In Orbit Selection, Anthony J. Correale
Theses and Dissertations
Low Earth Orbit (LEO) is becoming more congested, which increases the risk to space missions. Decision makers will need to consider this increase in congestion as an increased risk within their mission engineering process. This thesis proposes a methodology to create and implement a value structure that quantitatively scores a range of orbits based on congestion factors of each orbit and how well each orbit meets mission requirements. This thesis demonstrates this methodology on a set of circular LEO orbits defined by altitude and inclination, and scores this illustrative scenario based on notional mission measures and expected number of encounters …
The Cyber Wargame Commodity Course Of Action Automated Analysis Method, Alex Hoffendahl
The Cyber Wargame Commodity Course Of Action Automated Analysis Method, Alex Hoffendahl
Theses and Dissertations
In the modern operational landscape, strategic decisions are made and executed, under uncertain conditions, with many potential constraints and limited information. The end goal of these decisions is to minimize and mitigate the effect of adversarial threats, which may or may not act in line with previous assumptions. Wargaming is a powerful tool that allows for the practical implementation of theoretical knowledge into real-world scenarios, enhancing decision-makers critical thinking and problem solving skills. Furthermore, including cyber-effects in a wargame leads to a broader decision scope for an entire operation. This research aims to enhance the analytical capabilities and overall usability …
Optimal Aircraft Maneuvering Models For Cruise Missile Engagement: A Modeling And Computational Study, Izaiah G. Laduke
Optimal Aircraft Maneuvering Models For Cruise Missile Engagement: A Modeling And Computational Study, Izaiah G. Laduke
Theses and Dissertations
Given the increased threat and proliferation of adversary military capabilities, this research seeks to develop reasonably accurate and computationally tractable models to optimally maneuver aircraft to intercept cruise missile attacks. The research leveraged mathematical programming to model the problem, informed by constraints representing a system of (temporal) difference equations. The research began by comparing six models having alternative representations of velocity and acceleration constraints while analyzing situations with stationary targets. The Multiple Aircraft, Multiple Stationary Target Engagement Problem with Box Constraint Bounds (MAMSTEP-BC) Model yielded superior overall performance and was further analyzed through alternative mathematical programming model enhancements to create …
Analysis Of Container Shipments For Ustranscom, John N. Campos Y Campos
Analysis Of Container Shipments For Ustranscom, John N. Campos Y Campos
Theses and Dissertations
USTRANSCOM (United States Transportation Command) sends containers to various overseas destinations, mainly commercial container shipping companies. Delivering the containers to the destinations on time is important to support the United States (US) Forces deployed in foreign countries. This study analyzes container shipment records for two years from 2019 to 2021 and prepares insights for USTRANSCOM. This study utilizes descriptive statistics, data visualization, and one-way analysis of variance (ANOVA). According to the records, almost half of the containers (41.25%) were delivered late for one day or longer. The container with the longest delay took 408 days. Major reasons for delays included …
Military Personnel Flight Customer Wait Time Reduction Model Using Simulation, Nicholas C. Anderson
Military Personnel Flight Customer Wait Time Reduction Model Using Simulation, Nicholas C. Anderson
Theses and Dissertations
Customers at Military Personnel Flights (MPFs) have been experiencing long wait times. These customers are typically employees of the United States Air Force and every moment spent waiting for service is a moment they are away from their actual jobs. By reducing the mean wait time of MPF customers, manhours can be saved and customer complaints may be alleviated. This research uses data collected from an MPF to build a discrete-event simulation model of an MPF. A full factorial experimental design was conducted in the model using five factors. The factors included the total number of employees, the total number …
A Decision Support Simulation To Analyze Scheduling Alternatives For Applicant Processing At Military Entrance Processing Stations (Meps), Jonathan M. Escamilla
A Decision Support Simulation To Analyze Scheduling Alternatives For Applicant Processing At Military Entrance Processing Stations (Meps), Jonathan M. Escamilla
Theses and Dissertations
Applicant processing at Military Entrance Processing Stations (MEPS) is conducted via a batch arrival process by which all applicants arrive at the beginning of the processing day. Pursuit of alternate processing scenarios has never progressed beyond the pilot stage, possibly because the Command lacks a general decision support model to evaluate the impacts of proposed policies on applicant processing operations. This research creates a discrete event simulation of MEPS applicant processing operations and applies the model to three alternative applicant processing scenarios: split-shift, appointment- based, and express-lane. Results are examined and compared to benchmarks using multiple performance measurements.
Narrative Analysis Of Open-Source Social Media Activity In The Indopacom Aor, Aaron K. Glenn
Narrative Analysis Of Open-Source Social Media Activity In The Indopacom Aor, Aaron K. Glenn
Theses and Dissertations
Emotion classification can be a powerful tool to derive narratives from social media data. Recurrent Neural Networks (RNN) can meet or exceed the performance of state-of-the-art traditional machine learning techniques using exclusively open-source data and models. Specifically, these results show that RNN variants can produce more than an 8% gain in accuracy in comparison to Logistic Regression and SVM techniques and a 15% gain over Random Forest when using FastText embeddings. This research found a statistical significance in the performance of a single layer Bi-directional Long Short-Term Memory (Bi-LSTM) model over a 2-layer stacked Bi-LSTM model. This research also found …
Training Logic And Random Forest Models To Predict It Spending, Jacob P. Batt
Training Logic And Random Forest Models To Predict It Spending, Jacob P. Batt
Theses and Dissertations
The Air Force must modernize, but the distribution of funds for technology remains as tight as ever. To this end, the Air Force Audit Agency is looking to utilize machine learning techniques to enhance their capabilities. This research explores Logistic Regression and Random Forest modeling to streamline data collection and cost classification. The final Logistic Regression model identified 4 significant attributes out of the 36 given and was 85 accurate in predicting whether a purchase amount was over or under $10,000. To expand beyond binary classification, a six-category classification Random Forest model was developed. It identified 6 significant attributes and …
Combat Assessment For The Simulation Of Warfare, Benjamin L. Finch
Combat Assessment For The Simulation Of Warfare, Benjamin L. Finch
Theses and Dissertations
Military assessment seeks to answer two primary questions: "are we creating the effects that we desire?" and "are we accomplishing tasks to standard?" This thesis steps through several desirable characteristics for a simulated combat assessment methodology. After developing a value hierarchy from these characteristics, this thesis provides and evaluates several candidate methodologies for use within a combat simulation. Each alternative's evaluation is informed by its application to a small combat simulation. Upon recommending the use of Linear Programming, we utilize value-focused thinking to modify this alternative. The thesis terminates with some conclusory thoughts and ideas for future research.
Using Custom Ner Models To Extract Dod Specific Entities From Contracts, Kayla P. Haberstich
Using Custom Ner Models To Extract Dod Specific Entities From Contracts, Kayla P. Haberstich
Theses and Dissertations
The Air Force Sustainment Center collected 3.7 million contracts onto the Air Force Research Laboratory’s high power computers. They are in the format of a .pdf or scanned document, making them unstructured data. The Data Analytics Resource Team extracted the documents into a textual format for use in further analysis. This thesis looks to extract four DOD specific entities (NSN, Part Number, CAGE Code, and Supplier Name) from the contracts using custom NER models. This newly extracted information will allow the Air Force to identify what parts are supplied by which vendors. This information along with historical CLIN pricing for …
Enterprise Resource Allocation For Intruder Detection And Interception, Adam B. Haywood
Enterprise Resource Allocation For Intruder Detection And Interception, Adam B. Haywood
Theses and Dissertations
This research considers the problem of an intruder attempting to traverse a defender's territory in which the defender locates and employs disparate sets of resources to lower the probability of a successful intrusion. The research is conducted in the form of three related research components. The first component examines the problem in which the defender subdivides their territory into spatial stages and knows the plan of intrusion. Alternative resource-probability modeling techniques as well as variable bounding techniques are examined to improve the convergence of global solvers for this nonlinear, nonconvex optimization problem. The second component studies a similar problem but …
New Methods In Wavelet Analysis For Applications Of The Wavelet Transform, Jeffrey D. Williams
New Methods In Wavelet Analysis For Applications Of The Wavelet Transform, Jeffrey D. Williams
Theses and Dissertations
A commonality in the many applications and domains where signal processing (SP)is applied is the detection of events. Detection in SP requires the identification of the occurrence of an event, within a signal, and distinguishing the occurrence from no event. In a classical application of SP, seismologists seek to detect abnormalities in an electromagnetic (EM) signal to detect or not detect the occurrence of an earthquake, represented as an anomalous EM pulse. Since many signals are noisy, such as those produced by a seismograph, it can be challenging to distinguish a significant EM pulse from incident noise. In SP, smoothing …
Wavelet Methods For Very-Short Term Forecasting Of Functional Time Series, Jared K. Nystrom
Wavelet Methods For Very-Short Term Forecasting Of Functional Time Series, Jared K. Nystrom
Theses and Dissertations
Space launch operations at Kennedy Space Center and Cape Canaveral Space Force Station (KSC/CCSFS) are complicated by unique requirements for near-real time determination of risk from lightning. Lightning forecast weather sensor networks produce data that are noisy, high volume, and high frequency time series for which traditional forecasting methods are often ill-suited. Current approaches result in significant residual uncertainties and consequentially may result in forecasting operational policies that are excessively conservative or inefficient. This work proposes a new methodology of wavelet-enabled semiparametric modeling to develop accurate and timely forecasts robust against chaotic functional data. Wavelets methods are first used to …
Deep Learning For Weather Clustering And Forecasting, Nathaniel R. Beveridge
Deep Learning For Weather Clustering And Forecasting, Nathaniel R. Beveridge
Theses and Dissertations
Clustering weather data is a valuable endeavor in multiple respects. The results can be used in various ways within a larger weather prediction framework or could simply serve as an analytical tool for characterizing climatic differences of a particular region of interest. This research proposes a methodology for clustering geographic locations based on the similarity in shape of their temperature time series over a long time horizon of approximately 11 months. To this end an emerging and powerful class of clustering techniques that leverages deep learning, called deep representation clustering (DRC), are utilized. Moreover, a time series specific DRC algorithm …
Analysis Of The Effects Of Spatiotemporal Demand Data Aggregation Methods On Distance And Volume Errors, Zachary Hornberger, Bruce A. Cox, Raymond R. Hill
Analysis Of The Effects Of Spatiotemporal Demand Data Aggregation Methods On Distance And Volume Errors, Zachary Hornberger, Bruce A. Cox, Raymond R. Hill
Faculty Publications
Purpose — Large/stochastic spatiotemporal demand data sets can prove intractable for location optimization problems, motivating the need for aggregation. However, demand aggregation induces errors. Significant theoretical research has been performed related to the modifiable areal unit problem and the zone definition problem. Minimal research has been accomplished related to the specific issues inherent to spatiotemporal demand data, such as search and rescue (SAR) data. This study provides a quantitative comparison of various aggregation methodologies and their relation to distance and volume based aggregation errors. Design/methodology/approach — This paper introduces and applies a framework for comparing both deterministic and stochastic aggregation …
Developing A Basic Formal Supply Chain Ontology To Improve Communication And Interoperability, David Morrow
Developing A Basic Formal Supply Chain Ontology To Improve Communication And Interoperability, David Morrow
Theses and Dissertations
Information is crucial to supply chain performance because it is used to make decisions and trigger actions. Organizations across world-class supply chains increasingly use information technology to analyze and process supply chain data. However, supply chain management lacks a common language, making information exchange difficult. An ontology can provide a standardized framework that organizes a given knowledge domain. This research proposes a common language for developing a supply chain ontology that can be built into a basic formal ontology understood by both humans and computers. According to current research, an established and widely used supply chain framework is a good …
Strategic Upgrade Scheduling And Portfolio Management To Fortify Contested Networks, Justin L. Anderson
Strategic Upgrade Scheduling And Portfolio Management To Fortify Contested Networks, Justin L. Anderson
Theses and Dissertations
The nuclear command, control, and communication (NC3) network provides an effective deterrent against adversaries by maintaining robust communication between assets, operators, and decision makers. NC3 must receive a series of upgrades to remain an effective deterrent against evolving threats around the globe. Given a contested network and a portfolio of network upgrades, this research seeks an optimal upgrade schedule to maximize network resilience in support of NC3 modernization. Our research contributes a model that solves a budget-constrained network upgrade scheduling problem (NUSP). The NUSP is a defender-attacker-defender tri-level optimization model that achieves fortification via selecting and scheduling network upgrades. The …
Predicting F-16 Cause Code H Micap Hours Using Jmp Regression Analysis, Scott E. Carr
Predicting F-16 Cause Code H Micap Hours Using Jmp Regression Analysis, Scott E. Carr
Theses and Dissertations
Emergency demands for aircraft parts, MICAPs (Mission Impaired Capability Awaiting Parts) are one of the leading issues affecting mission capability supply rates for fighter aircraft. Cause code H MICAPS, those with a known demand level, but no supply available, are particularly troublesome and difficult to resolve. These MICAPS are due to failures by the supply chain to replenish stock levels within acceptable time limits. Numerous studies have identified a clear need for proactive measures to reduce MICAP hours. This would significantly improve aircraft availability. This study uses regression analysis implemented in JMP software to build models with a goal of …
Air Combat Maneuvering Via Operations Research And Artificial Intelligence Methods, James B. Crumpacker
Air Combat Maneuvering Via Operations Research And Artificial Intelligence Methods, James B. Crumpacker
Theses and Dissertations
Within visual range air combat requires rapid, sequential decision-making to survive and defeat the adversary. Fighter pilots spend years perfecting maneuvers for these types of engagements, yet the emergence of unmanned, autonomous vehicle technologies elicits a natural question - can an autonomous unmanned combat aerial vehicle (AUCAV) be imbued with the necessary artificial intelligence to perform air combat maneuvering tasks independently? We formulate and solve the air combat maneuvering problem to examine this question, developing a Markov decision process model to control an AUCAV seeking to destroy a maneuvering adversarial vehicle. An approximate dynamic programming (ADP) approach implementing neural network …
Exploring The Limits Of Strategic Thought: Evaluating How Different Communication Modalities Affect The Nature Of Strategic Decision-Making Using Cognitive Hierarchy, Stephen D. Donnel
Exploring The Limits Of Strategic Thought: Evaluating How Different Communication Modalities Affect The Nature Of Strategic Decision-Making Using Cognitive Hierarchy, Stephen D. Donnel
Theses and Dissertations
This research examines and quantifies the degree to which both information communication modality and the situational complexity affect individuals' ability to process the provided information and determine an effective strategy. Human subject testing herein consists of benign benevolent intervention involving the presentation of a series of strategic situations. For each situation, a participant attempts to identify their best response for a two-player, normal-form game with complete information. In each such game, players seek to maximize their own utility while considering their own actions, their opponent's actions, and each player's respective preferences over outcomes resulting from the possible combinations of actions. …
An Examination Of Potential Training Regression Recognition Algorithms For Pilot Training Next, Alex R. Gaines
An Examination Of Potential Training Regression Recognition Algorithms For Pilot Training Next, Alex R. Gaines
Theses and Dissertations
The initiative to reduce the Air Forces serious pilot shortage lead to the Pilot Training Next (PTN) program. Under PTN, student pilots progress at an individual rate while making increased use of simulator-based training resources. A previous thesis used data from the first PTN class to conceptualize and prototype a student training flight scheduler. This scheduler did not consider training events required to bring students back to achieved levels of performance if in fact that student performance had regressed. This thesis examines three classes of PTN student data to determine whether student regression in training progression can be detected. A …