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Articles 1 - 30 of 1247
Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Modeling Individual Self-Protective Behavior During Epidemics, Geonsik Yu, Michael J. Garee, Mario Ventresca, Yuehwern Yih
Modeling Individual Self-Protective Behavior During Epidemics, Geonsik Yu, Michael J. Garee, Mario Ventresca, Yuehwern Yih
Faculty Publications
Protecting public health from infectious diseases requires collective action, as individual behaviors—such as vaccination and mask-wearing—directly influence disease dynamics. During the COVID-19 pandemic, unexpected public responses often undermined the effectiveness of interventions, highlighting the need to understand collective behavioral patterns and motivations to design more effective mitigation strategies. This study presents an agent-based simulation model that captures how individuals adjust self-protective behaviors based on evolving opinions about disease risk and examines how these decisions interact with external factors, such as public health interventions, to shape collective outcomes. To improve the representativeness of the simulated population, multiple datasets were integrated to …
Optimizing Warranty Policies For Remanufactured Products: When Should They Be Longer, Shorter, Or Identical To New Product Warranties?, Kunpeng Li, Jun-Yeon Lee
Optimizing Warranty Policies For Remanufactured Products: When Should They Be Longer, Shorter, Or Identical To New Product Warranties?, Kunpeng Li, Jun-Yeon Lee
Faculty Publications
Manufacturers adopt different warranty strategies for remanufactured products, offering shorter, identical, or longer warranty periods compared to new products. However, prior research has only focused on manufacturers offering either shorter or identical warranties. In addition, the existing literature has not captured the diminishing returns of warranties, i.e., as the warranty coverage increases, its incremental benefits begin to decrease but the costs continue to increase. To address these gaps, we develop an optimization model that jointly considers pricing and warranty decisions while accounting for warranty’s diminishing effect on consumer’s willingness to pay for remanufactured products. We show that all three observed …
Analogy2kg: An Automatic Pipeline For Deriving Knowledge Graphs From Long-Text Analogies, Kara Combs, Lance E. Champagne, Bruce A. Cox, Christine M. Schubert Kabban, Trevor Bihl, Grace Lemming
Analogy2kg: An Automatic Pipeline For Deriving Knowledge Graphs From Long-Text Analogies, Kara Combs, Lance E. Champagne, Bruce A. Cox, Christine M. Schubert Kabban, Trevor Bihl, Grace Lemming
Faculty Publications
Analogical reasoning is an increasingly popular, lightweight solution to enable large language model (LLM)-level reasoning without computational complexity. Still, it has yet to be adopted due to its reliance on strictly hand-formatted data. Therefore, we propose Analogy2KG (“Analogy to Knowledge Graph”), as an automatic pipeline that transforms text into a KG format via a fine-tuned version of information extraction (IE) algorithms for long-text analogies. The need to verify that the complex underlying analogical structure of the data is maintained was done via paired samples tests in the creation and validation of this pipeline. Graph density was used to evaluate the …
Implementing Lean Principles To Enhance Warehouse Operations At King Abdulaziz Air Base(Kaab): A Case Study Of Royal Saudi Air Force (Rsaf), Saleh A. Alghamdi
Implementing Lean Principles To Enhance Warehouse Operations At King Abdulaziz Air Base(Kaab): A Case Study Of Royal Saudi Air Force (Rsaf), Saleh A. Alghamdi
Theses and Dissertations
The Royal Saudi Air Force (RSAF) relies on efficient logistics to sustain readiness. At King Abdulaziz Air Base, warehouse receiving inefficiencies caused delays and waste. This study used Lean principles and a six-month time–motion analysis, with Pareto and Fishbone tools, to identify 55% waste in dead pile and 75% in palletized shipments. Standard times of 5.98 and 6.55 minutes were set. Key recommendations include SOPs, cross-training, forklift certification, layout redesign, and RFID. Lean adoption could save 100+ labor hours and $4,000 annually, improving safety, accuracy, and mission readiness.
A Review Of The United States' Long Term War Support Capabilities In The Indo-Pacific Command Region, Brian J. Mullin Jr.
A Review Of The United States' Long Term War Support Capabilities In The Indo-Pacific Command Region, Brian J. Mullin Jr.
Theses and Dissertations
This study examines U.S. maritime transportation readiness in the Indo-Pacific, highlighting fleet age, mariner shortages, shipyard decline, and port vulnerabilities. It also considers contested logistics and technological threats. Recommendations include fleet recapitalization, mariner pipeline growth, port diversification, and defensive upgrades. The study concludes that secure sea line assumptions are outdated and calls for greater resilience, with follow-on efficiency analysis proposed for ports and ships.
Automation Of Lcmc Logistics Processes: A Delphi Approach, Kline M. Alt
Automation Of Lcmc Logistics Processes: A Delphi Approach, Kline M. Alt
Theses and Dissertations
As the U.S. Air Force confronts growing complexity in system acquisition, the implementation of digital models in system design and logistics process management allows the incorporation of digital tools and the possibility for automation of portions of logistics processes. This thesis investigates where these technologies can be most effectively integrated within the Air Force Life Cycle Management Center logistics enterprise (AFLCMC). Using a three round Delphi study, AFLCMC logistics subject matter expert (SME) opinions were solicited from program-level senior logisticians, program managers to identify high-need areas, key success factors, and potential barriers to adoption. Quantitative consensus from Likert-scale and ordinal …
Köppen-Geiger Climate Effects On F-15 Readiness Spares Package Parts, Maximus A. Fan
Köppen-Geiger Climate Effects On F-15 Readiness Spares Package Parts, Maximus A. Fan
Theses and Dissertations
Readiness Spares Packages (RSP) are critical to deployed operations. Future demands of the Air Force require squadrons to operate in different climate environments from home stations. RSPs can sustain aircraft maintenance operations for up to 30 days. Currently, failure rates of parts within the RSP are assumed to be constant. This research aims to explore whether there is a difference in F-15 RSP failure rates when Koeppen climate classifications are taken into effect. The Koeppen-Geiger system classifies area climates based on the geography, elevation, and location. The history of operations and diversity of F-15 locations make the aircraft an ideal …
Advancing Autonomous Swarm Behavior In A Simulated Anti-Access Area Denial Environment, Chad Macwilkinson, Lance E. Champagne, Phillip M. Lacasse
Advancing Autonomous Swarm Behavior In A Simulated Anti-Access Area Denial Environment, Chad Macwilkinson, Lance E. Champagne, Phillip M. Lacasse
Faculty Publications
This study proposes the application of a four dimensional framework of autonomy to a weapon swarm of high subsonic cruise missiles.
War, Wounds, And Strategy: Patient Movement Lessons From The World Wars For Great Power Competition, Phillip R. Jenkins
War, Wounds, And Strategy: Patient Movement Lessons From The World Wars For Great Power Competition, Phillip R. Jenkins
Faculty Publications
This thesis examines the evolution of the U.S. military's patient movement system during World War I and World War II to evaluate how well it may perform under the conditions of future large-scale combat operations. It asks whether the United States can move, treat, and sustain wounded personnel at the scale and pace required to preserve combat power in a prolonged, high-intensity conflict. Using detailed case studies of the Meuse-Argonne Offensive and the Battle of the Bulge, the analysis focuses on how transportation platforms, organizational structure, and standard operating procedures (SOPs) shaped patient movement under conditions of attrition, disruption, and …
Rotating Scatter Mask System Optimization Study For Determining Optimal Image Recreation, Seth L. Grover
Rotating Scatter Mask System Optimization Study For Determining Optimal Image Recreation, Seth L. Grover
Theses and Dissertations
The Rotating Scatter Mask (RSM) system is a radiation imaging technology currently limited by the mask design and governing identification algorithm parameters. To optimize the RSM design, Dakota—an optimization software—was integrated with a ray tracing code that simulates particle interactions with the RSM detector, and with the Locally Competitive Algorithm (LCA), which reconstructs the source image based on the ray tracing code’s Detector Response Matrix (DRM). Since the original ray tracing code was developed in MATLAB, it was translated into Python to improve compatibility with both Dakota and LCA. The Python version of the ray tracing code was then integrated …
Contract Quality Feature Extraction Using Llm, Aaron C. Washington
Contract Quality Feature Extraction Using Llm, Aaron C. Washington
Theses and Dissertations
This study explored the potential insights generated from linguistic complexity measurements and large language model (LLM) based assessments on the quality of contract documents. By combining structured True/False prompts with log-probability analysis and ambiguity scoring, the study introduced novel contract-quality assessment methods. Results support a feature-driven approach to contract evaluation, one that offers automated, scalable insights for triaging risk and improving drafting practices. These assessment methods contribute to the growing field of legal natural language processing by offering modular tools for effective contract analysis.
Modeling And Characterization Of On-Orbit Servicing Architectures For Efficient Mission Planning, Samantha Q. Vi Tang
Modeling And Characterization Of On-Orbit Servicing Architectures For Efficient Mission Planning, Samantha Q. Vi Tang
Theses and Dissertations
As space-based systems become increasingly critical to global infrastructure, efficient satellite maintenance and resource management have become essential to ensuring operational longevity. On-orbit servicing has emerged as a key strategy for extending satellite lifespans, mitigating space debris accumulation, and enhancing the cost effectiveness of space operations. This study presents a comprehensive mixed-integer programming (MIP) model to optimize servicer task assignments and routing while minimizing propellant consumption. The model captures the operational complexities of servicing a network of satellites across multiple orbits by incorporating realistic constraints, such as fuel limitations and task completion time windows. Sensitivity analysis allows mission planners to …
Operational Energy Education: A Thematic Analysis Of Knowledge Area Needs And Educational Gaps, Nana Hene
Operational Energy Education: A Thematic Analysis Of Knowledge Area Needs And Educational Gaps, Nana Hene
Theses and Dissertations
Operational Energy (OE) education is vital for national security, military readiness, and fuel energy efficiency. This thesis analyzes the current landscape of OE education and identifies key gaps in awareness, energy knowledge, and curriculum structure. Through a reflexive thematic analysis of interviews with Subject Matter Experts (SMEs), the study underscores the necessity of integrating OE concepts into both educational and professional training programs. A framework is proposed to enhance OE education across various levels in the Air Force, aiming to cultivate a more energy-conscious and strategically prepared force. The findings highlight the critical need for targeted training, curriculum enhancements, and …
Military Entrance Processing Station Location And Capacity Optimization, Micah A. Hurst
Military Entrance Processing Station Location And Capacity Optimization, Micah A. Hurst
Theses and Dissertations
This research optimizes the number, placement, and capacity of Military Entrance Processing Stations (MEPS) to minimize applicant and recruiter travel and improve recruitment efficiency. Using mixed-integer programming, it develops capacitated facility location (CFLP) and maximal covering location (MCLP) models, considering facility capacity, budget, and geographic coverage. Computational testing and scenario evaluations highlight opportunities to reduce travel and balance capacity. For example, the CFLP model adds three new MEPS, reducing annual applicant travel by 1.2 million miles in Florida and Texas and 1.0 million in California, while increasing accessibility within 60 miles of a MEPS. This data-driven approach provides USMEPCOM with …
The Location Set Covering Disruption Problem, Richard A. Sheldon
The Location Set Covering Disruption Problem, Richard A. Sheldon
Theses and Dissertations
This research models and analyzes a variant of the Location Set Covering Problem (LSCP) in a bilevel, game theoretic setting by posing the LSCP as a non-cooperative attacker-defender Stackelberg game, where facilities are to be emplaced by the defender from a boarder set of potential facility locations to cover a set of demands; however, an attacker removes the possibility of emplacing q specific facility locations with the objective to remove the maximum weighted value demands, and then lexicographically maximize the cost of coverage of remaining demands. A novel methodology leveraging lexicographic programming computed an optimal solution for 98% of all …
Impact Of Stochastic Travel Times On The Military Port Selection Problem: A Stochastic Programming Approach, William M. Titus
Impact Of Stochastic Travel Times On The Military Port Selection Problem: A Stochastic Programming Approach, William M. Titus
Theses and Dissertations
This research models and analyzes the impact of stochastic travel times on port selection during a large-scale mobilization of equipment from continental United States installations to deployment locations using sealift ships. A stochastic mixed-integer programming model is developed to minimize the average arrival time of equipment into theater. The model is solved using Sample Average Approximation. In the first stage, the model selects ports to open and assigns installations, equipment, and ships to open ports. In the second stage, travel times are realized, and equipment is assigned to specific ships that are scheduled to depart. Results show that the marginal …
Practical Estimation Of Action-Generation Mechanisms In Repeated Games, Vladimer Kellachow Iii
Practical Estimation Of Action-Generation Mechanisms In Repeated Games, Vladimer Kellachow Iii
Theses and Dissertations
The goal of this research is to gain insight into how players of a game learn their strategy during the course of repeated play. The study employs the Experience Weighted Attraction (EWA) model, developed by Dr. Colin F. Camerer and Dr. Teck-Hua Ho, as the foundational behavioral framework. Using historic observed strategy decisions, the parameter values that define an opponent’s learning process are updated using various inference methods.
Machine Learning Techniques To Detect Anomalies In T-38 Flight Sensor Data, Sydney M. Wekamp
Machine Learning Techniques To Detect Anomalies In T-38 Flight Sensor Data, Sydney M. Wekamp
Theses and Dissertations
Accurate sensors are critical for ensuring the safety of aircrew. However, detecting faulty sensors remains a significant challenge for the Test Pilot School at Edwards Air Force Base in California. Current methods rely on either student pilots identifying anomalies or waiting for sensors to fail completely before repairs are made—an approach that lacks reliability and consistency. This research aims to address these shortcomings by implementing machine learning techniques to detect sensor faults proactively. To date, applying machine learning to a dataset of this size, encompassing numerous sensors on the same aircraft, is unprecedented. The project focuses on establishing strong baseline …
A Case Study N Modeling The Human Behavior Of Basic Fighter Maneuvers Using Mbse, Josiah J. Franklin
A Case Study N Modeling The Human Behavior Of Basic Fighter Maneuvers Using Mbse, Josiah J. Franklin
Theses and Dissertations
As fighter aircraft become more complex and technology, such as autonomy, is introduced, it is essential to anticipate the critical tasks and information pilots need to accomplish their mission with these new systems. Fighter pilots operate in highly demanding situations where the consequences of failure are severe and require their systems to provide the right information for the task. Traditionally, these designs are informed through Critical Task Analyses of existing systems. This research produced a method for modeling critical task analysis and information requirements using model-based systems engineering. The scenario was a fighter aircraft conducting basic fighter maneuvers in a …
Spatiotemporal Prediction Of Atmospheric Events Through Recurrent Deep Learning Model, Brian W. F. Popick
Spatiotemporal Prediction Of Atmospheric Events Through Recurrent Deep Learning Model, Brian W. F. Popick
Theses and Dissertations
The main contributions of this research is to add to the growing library of literature on the use of deep learning algorithms for the spatiotemporal prediction of dangerous atmospheric and hydrologic phenomena. Specifically, we develop novel attention-based and non-attention-based recurrent neural network frameworks to produce short-range sequential forecasts for lightning and tornado occurrences. Additionally, we introduce methods that account for and include error in the model tuning process to generate more reliable models. Furthermore, we have created a lightweight spatiotemporal tornadic prediction dataset that we plan to make publicly available. The first component of this research develops three novel spatiotemporal …
Understanding Avionics Maintenance Training Student Outcomes In A Student-Centered Active Learning Environment, Scott M. Wyman
Understanding Avionics Maintenance Training Student Outcomes In A Student-Centered Active Learning Environment, Scott M. Wyman
Theses and Dissertations
This study examines the effects of active learning compared to didactic methodologies on two soft skills, namely teamwork and self-efficacy using regression analyses and connected letter reports. Learning styles and personality traits were used as predictors. Findings indicate significant interaction effects between methodology, aural learning style, and personality traits on self-efficacy and teamwork ability. The findings highlight the nuanced role of learner traits in shaping teamwork outcomes across instructional methods. While active learning supports soft skills, individual differences must be considered in instructional design to optimize teamwork in technical education settings.
The Application Of Decision Analysis Theory For Space Allocation At The Air Force Institute Of Technology, Damian N. Soriano
The Application Of Decision Analysis Theory For Space Allocation At The Air Force Institute Of Technology, Damian N. Soriano
Theses and Dissertations
This thesis investigates the application of Decision Analysis Theory to optimize space allocation at the Air Force Institute of Technology (AFIT). Through a Multi-Objective Decision Analysis (MODA) framework, this study addresses existing methodologies for space allocation in military, academic, and office settings; the rules, limitations, and factors influencing space utilization at AFIT; and approaches to improve office and lab allocations for institutional efficiency and fairness. This research incorporates qualitative and quantitative metrics, including faculty and student data, research outputs, and historical space usage. These findings highlight significant complexities in space allocation, particularly in reconciling administrative and research requirements with structural …
Simulating The Impact Of Self-Sensing Materials On Aircraft Sortie Generation, Harmoni J. Blackstock
Simulating The Impact Of Self-Sensing Materials On Aircraft Sortie Generation, Harmoni J. Blackstock
Theses and Dissertations
In conjunction with the Air Force Research Laboratory Materials Lab(AFRL-RX), this study evaluates the potential military value of the prototype material sensing composites on Unmanned Aerial Vehicle (UAV) operations in intelligence, surveillance, reconnaissance (ISR), and close air support (CAS) missions within a contested Indo-Pacific theater. Using a Simio based simulation,UAV performance was assessed under varying combat conditions, focusing on Remote Sensing, deployment strategies, initial lay-downs, and varying loss rates. Re-sults show that UAVs equipped with Remote Sensing technology significantly improved sortie generation and logistical efficiency. Scenario 17 achieved the highest sortie rate(965.5 sorties), outperforming the next-best scenario by 25 sorties. …
Evaluating Weather Effects On Sortie Generation Using Discrete Event Simulation, Markus Case
Evaluating Weather Effects On Sortie Generation Using Discrete Event Simulation, Markus Case
Theses and Dissertations
United States Air Force (USAF) operations rely on sortie generation, a complex system involving aircraft maintenance, operational planning, munitions, security forces, and aircrew. Failures in any of these areas can jeopardize a mission, and extreme weather events such as lightning, high winds, and snow further complicate operations. This thesis examines the impact of extreme weather on sortie generation, focusing on developing a data-driven discrete-event simulation (DES) to predict generation timelines and identify high-risk areas. The model allows users to adjust key inputs, including the month, number of aircraft, processing times, and personnel/equipment availability. By simulating real-world conditions, the model helps …
Class Imbalance: A Landscape Of Classification Models, Joshua L. Edmonds
Class Imbalance: A Landscape Of Classification Models, Joshua L. Edmonds
Theses and Dissertations
Class imbalance poses significant challenges in machine learning classification. This study evaluates the performance of seven models (ANN, k-Means, kNN, LDA, LR, SVM, XGBoost) across multiple imbalance levels (10\%, 5\%, 1 \%, 0.5\%) and investigates the effectiveness of sampling techniques (Undersampling, SMOTE, SMOTE-ENN). ANOVA results confirm that model choice is the most critical factor, with XGBoost and SVM demonstrating superior robustness. SMOTE improves recall but reduces precision, while undersampling generally degrades overall performance. While significant, imbalance levels do not play a critical role in model effectiveness.
Data Lakehouse And Machine Learning Pipeline For Aircraft Fuel Efficiency Experimentation, Skyler G. Kepley
Data Lakehouse And Machine Learning Pipeline For Aircraft Fuel Efficiency Experimentation, Skyler G. Kepley
Theses and Dissertations
Fuel efficiency is crucial for the U.S. Air Force, impacting mission success, aircraft performance, and cost savings. This study presents an information system that integrates flight and maintenance data using a data lakehouse. It automates ingestion, enrichment, and predictive modeling, leveraging AutoML for optimization and SHAP for transparency. A case study on C-130J aircraft shows that optimizing D Check cycles can save 11.52 pounds of fuel per flight hour. These findings highlight the effectiveness of data-driven decision-making in aviation, offering a scalable, automated solution for improving fuel efficiency and reducing costs.
Machine Learning With Flight Data Recorder Data For Flight Fuel Consumption Predictions, Adam C. Levandowski
Machine Learning With Flight Data Recorder Data For Flight Fuel Consumption Predictions, Adam C. Levandowski
Theses and Dissertations
This study applies advanced Machine Learning (ML) to Flight Data Recorder (FDR) data for fuel consumption predictions. It explores feature engineering, model selection, and Hyper-Parameter Optimization (HPO) across all flight phases. Baseline models like Ordinary Least Squares (OLS) regression, Multi- Layer Perceptrons (MLPs), and decision trees are compared to Deep Neural Networks (DNNs), Recurrent Neural Networks (RNNs) with Gated Recurrent Unit (GRU) layers, and XGBoost. Results analyze segmentation strategies, tailored features, and model performance. A counterfactual analysis compares ML models to operational fuel predictions, demonstrating their deployment potential. Findings establish a foundation for future ML-driven advancements in aviation fuel optimization.
Island Nation Duress: Simulating Passive Peer-To-Peer Bluetooth Communication During Disaster Relief, Jason K. Medeiros
Island Nation Duress: Simulating Passive Peer-To-Peer Bluetooth Communication During Disaster Relief, Jason K. Medeiros
Theses and Dissertations
Pacific Islands under U.S. jurisdiction are highly vulnerable to natural disasters, yet many lack the infrastructure to effectively respond and recover. Clear communication during and after such events is critical for evacuation, hazard awareness, and first responders’ coordination. This research explores a simulation-based approach using Bluetooth communication to relay messages across Guam, assessing its efficiency through statistical analysis. By examining regional differences and geographic impacts on Bluetooth messaging, the study aims to identify key factors that enhance peer-to-peer communication for timely and effective disaster response.
Real-Time Decision-Making During Maritime Chokepoint Disruption Using Digital Twin, Jared M. Orendorff
Real-Time Decision-Making During Maritime Chokepoint Disruption Using Digital Twin, Jared M. Orendorff
Theses and Dissertations
This research develops a digital twin of the global maritime shipping system to model disruptions in major shipping lanes like the Suez and Panama Canals. By incorporating live ship-tracking data, the model simulates closures, forecasts queue lengths, and determines the best rerouting options. Findings show that canal closures cause large traffic backlogs and increased congestion at alternative chokepoints, while rerouted ships may face higher piracy risks in regions like the Gulf of Guinea and the Strait of Malacca. This tool helps decision-makers respond effectively to maritime disruptions.
Utility Of Self-Sensing Damage Technology Through A2/Ad Drone Combat Simulation, Sidhanth Venkatasubramaniam
Utility Of Self-Sensing Damage Technology Through A2/Ad Drone Combat Simulation, Sidhanth Venkatasubramaniam
Theses and Dissertations
Since the introduction of the first unmanned aerial vehicle (UAV), UAVs have consistently improved in capability and versatility. The ability to perform military operations without the risk of losing human life is crucial for the United States military. The trade-off for this versatility is cost, and several ongoing research efforts are being made to improve UAV mission success and the lifespan of UAVs. An area of research that falls under the categories mentioned is self-damage detection. The Air Force Research Laboratories (AFRL) are developing a capability to enable a UAV to assess airframe damage, enabling real-time determination of damage potentially …