Comparing Actively Managed Mutual Fund Categories To Index Funds Using Linear Regression Forecasting And Portfolio Optimization,
2022
University of Arkansas, Fayetteville
Comparing Actively Managed Mutual Fund Categories To Index Funds Using Linear Regression Forecasting And Portfolio Optimization, Luke Weiner
Industrial Engineering Undergraduate Honors Theses
The global investment industry offers a wide variety of investment products especially for individual investors. One such product, index funds, which are younger than actively managed mutual funds, have typically outperformed managed funds. Despite this phenomenon, investors have displayed a tendency to continue investing in actively managed funds. Although only a small percentage of actively managed funds outperform index funds, the costs of actively managed funds are significantly higher. Also, managed fund performances are most often determined by their fund category such as growth or real estate. I wanted to answer the following question for individual investors: can we …
A Study Of Scheduling Problems With Sequence Dependent Restrictions And Preferences,
2022
Clemson University
A Study Of Scheduling Problems With Sequence Dependent Restrictions And Preferences, Nitin Srinath
All Dissertations
In some applications like fabric dying, semiconductor wafer processing, and flexible manufacturing, the machines being used to process jobs must be set up and serviced frequently. These setup processes and associated setup times between jobs often depend on the jobs and the sequence in which jobs are placed onto machines. That is, the scheduling of jobs on machines must account for the sequence-dependent setup times as well. These setup times can be a major factor in operational costs. In fabric dyeing processes, the sequence in which jobs are processed is also important for quality, i.e., there is a strong preference …
Forecasting Hypotension By Learning From Multivariate Mixed Responses..,
2022
University of Louisville
Forecasting Hypotension By Learning From Multivariate Mixed Responses.., Jodie Ritter
Electronic Theses and Dissertations
Blood Pressure is the main determinant of blood flow to organs. Hypotension is defined as a systolic blood pressure less than 90 mmHg or a diastolic blood pressure less than 50 mmHg. The severity and duration of hypotension is associated with low blood flow to organs often result in organ damage and a high mortality rate. Predicting hypotension prior to surgery and during the surgery can reduce the incidence and duration resulting in better patient outcomes. This thesis uses preoperative bloodwork and vital signs as well as perioperative vital signs in 5-minute increments as inputs to forecast hypotension. Hypotension can …
Finding Core Members Of A Hedonic Game,
2022
Old Dominion University
Finding Core Members Of A Hedonic Game, Daniele M. Vernon-Bido
Computational Modeling & Simulation Engineering Theses & Dissertations
Agent-based modeling (ABM) is a frequently used paradigm for social simulation; however, there is little evidence of its use in strategic coalition formations. There are few models that explore coalition formation and even fewer that validate their results against an expected outcome. Cooperative game theory is often used to study strategic coalition formation but solving games involving a significant number of agents is computationally intractable. However, there is a natural linkage between ABM and the study of strategic coalition formation. A foundational feature of ABM is the interaction of agents and their environment. Coalition formation is primarily the result of …
Complex System Governance Leadership,
2022
Old Dominion University
Complex System Governance Leadership, David C. Walters
Engineering Management & Systems Engineering Theses & Dissertations
The purpose of this research was to develop a systems theory-based framework for leadership in governance of complex systems. Recognizing complexity and uncertainty as norms for the environments in which organizations exist encouraged researchers to suggest complexity theory, complex systems, and complex adaptive systems as appropriate for addressing these conditions. Complex System Governance (CSG), based in systems theory, management cybernetics, and governance, endeavors to provide for the design, execution and evolution of functions that provide control, communication, coordination, and integration at the metasystem level to support operations and continued system existence (viability). From a management cybernetics perspective, CSG leadership has …
Predicting The Likelihood And Scale Of Wildfires In California Using Meteorological And Vegetation Data,
2022
University of Arkansas, Fayetteville
Predicting The Likelihood And Scale Of Wildfires In California Using Meteorological And Vegetation Data, Matthew Walters
Graduate Theses and Dissertations
Wildfires have devastating ecological, environmental, economical, and public health impacts through the deterioration of water and air quality, CO2 emissions, property damage, and lung illnesses. The early detection and prevention of wildfires allow for the minimization of these risks. The use of Artificial Intelligence (AI) in wildfire detection and prediction has been highly researched as a tool to assist firefighters in stopping wildfires in its early stages. The three common wildfire prediction categories include image and video detection, behavior prediction, and susceptibility prediction. Data such as climate, weather, vegetation, satellite images, and historical wildfire data is most commonly used. Many …
The Impact Of Reliability In Conceptual Design - An Integrated Trade-Off Analysis,
2022
University of Arkansas, Fayetteville
The Impact Of Reliability In Conceptual Design - An Integrated Trade-Off Analysis, Tevari James Barker
Graduate Theses and Dissertations
Research presented in this paper focuses on developing models to estimate the systemreliability of Unmanned Ground Vehicles using knowledge and data from similar systems. Traditional reliability approaches often require detailed knowledge of a system and are used in later design stages as well as development, operational test and evaluation, and operations. The critical role of reliability and its impact on acquisition program performance, cost, and schedule motivate the need for improved system reliability models in the early design stages. Reliability is often a stand-alone requirement and not fully included in performance and life cycle cost models. This research seeks to …
Factors Affecting Hotel Recommendation: Before The Covid-19 Pandemic And After The Reopening,
2022
University of Nevada, Las Vegas
Factors Affecting Hotel Recommendation: Before The Covid-19 Pandemic And After The Reopening, Boran Kim
UNLV Theses, Dissertations, Professional Papers, and Capstones
During the COVID-19 pandemic, numerous people lost their lives, and a lot of industries were affected. The hospitality industry was especially affected due to social distancing, travel restrictions, and safety issues. During that time, not only did customers' expectations change but their recommendation of hotels to friends and colleagues also changed. The current study used five factors (i.e., cleanliness, location, room, service, and value) to discover which factors were affecting hotel recommendation before the COVID-19 pandemic and after the reopening. This study used secondary data (online surveys) from one of the well-known integrated resorts located in the western United States. …
An Elliptical Cover Problem In Drone Delivery Network Design And Its Solution Algorithms,
2022
Wayne State University
An Elliptical Cover Problem In Drone Delivery Network Design And Its Solution Algorithms, Yanchao Liu
Industrial and Systems Engineering Faculty Research Publications
Given n demand points in a geographic area, the elliptical cover problem is to determine the location of p depots (anywhere in the area) so as to minimize the maximum distance of an economical delivery trip in which a delivery vehicle starts from the nearest depot to a demand point, visits the demand point and then returns to the second nearest depot to that demand point. We show that this problem is NP-hard, and adapt Cooper’s alternating locate-allocate heuristic to find locally optimal solutions for both the point-coverage and area-coverage scenarios. Experiments show that most locally optimal solutions perform similarly …
The Traveling Salesman Problem: An Analysis And Comparison Of Metaheuristics And Algorithms,
2022
Liberty University
The Traveling Salesman Problem: An Analysis And Comparison Of Metaheuristics And Algorithms, Mason Helmick
Senior Honors Theses
One of the most investigated topics in operations research is the Traveling Salesman Problem (TSP) and the algorithms that can be used to solve it. Despite its relatively simple formulation, its computational difficulty keeps it and potential solution methods at the forefront of current research. This paper defines and analyzes numerous proposed solutions to the TSP in order to facilitate understanding of the problem. Additionally, the efficiencies of different heuristics are studied and compared to the aforementioned algorithms’ accuracy, as a quick algorithm is often formulated at the expense of an exact solution.
Multiagent Routing Problem With Dynamic Target Arrivals Solved Via Approximate Dynamic Programming,
2022
Air Force Institute of Technology
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 …
Bayesian Convolutional Neural Network With Prediction Smoothing And Adversarial Class Thresholds,
2022
Air Force Institute of Technology
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 …
Analysis Of Container Shipments For Ustranscom,
2022
Air Force Institute of Technology
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 …
Team Air Combat Using Model-Based Reinforcement Learning,
2022
Air Force Institute of Technology
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 …
Air Force Specialty Code Assignment Optimization,
2022
Air Force Institute of Technology
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 …
Military Personnel Flight Customer Wait Time Reduction Model Using Simulation,
2022
Air Force Institute of Technology
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),
2022
Air Force Institute of Technology
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.
An Exploratory Analysis Of Time Series Econometric Data For Retention Forecasting Using Deep Learning,
2022
Air Force Institute of Technology
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 …
Screening Heuristics For The Evaluation Of Covert Network Node Insertion Scenarios,
2022
Air Force Institute of Technology
Screening Heuristics For The Evaluation Of Covert Network Node Insertion Scenarios, Andrew E. Pekarek
Theses and Dissertations
The majority of research on covert networks uses social network analysis (SNA) to determine critical members of the network to either kill or capture for the purpose of network destabilization. This thesis takes the opposite approach and evaluates potential scenarios for inserting an agent into a covert network for information gathering purposes or future disruption operations. Due to the substantial number of potential insertion scenarios in a large network, this research proposes three screening heuristics that leverage SNA measures to reduce the solution space before applying a simple search heuristic.
Optimal Aircraft Maneuvering Models For Cruise Missile Engagement: A Modeling And Computational Study,
2022
Air Force Institute of Technology
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 …
