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Operations Research, Systems Engineering and Industrial Engineering

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Comparing North American Professional Sports League Season Formats Using Monte Carlo Simulation, Lathan Gregg May 2024

Comparing North American Professional Sports League Season Formats Using Monte Carlo Simulation, Lathan Gregg

Industrial Engineering Undergraduate Honors Theses

Each NFL, NBA, and MLB season consists of a regular season, in which teams play a set number of scheduled games and a playoff, in which qualifying teams compete for a championship. At the conclusion of each season, teams are ranked based on their performance throughout the season. This study aims to investigate the ability of each league's season format to accurately rank teams using Monte Carlo simulation. Matches between two teams are simulated by using the team’s assigned strength ranks to calculate a winning probability for each team. The winning probabilities are simulated with different skill values, dictating how …


Cost-Risk Analysis Of The Ercot Region Using Modern Portfolio Theory, Megan Sickinger May 2024

Cost-Risk Analysis Of The Ercot Region Using Modern Portfolio Theory, Megan Sickinger

Master's Theses

In this work, we study the use of modern portfolio theory in a cost-risk analysis of the Electric Reliability Council of Texas (ERCOT). Based upon the risk-return concepts of modern portfolio theory, we develop an n-asset minimization problem to create a risk-cost frontier of portfolios of technologies within the ERCOT electricity region. The levelized cost of electricity for each technology in the region is a step in evaluating the expected cost of the portfolio, and the historical data of cost factors estimate the variance of cost for each technology. In addition, there are several constraints in our minimization problem to …


Stability Of Quantum Computers, Samudra Dasgupta May 2024

Stability Of Quantum Computers, Samudra Dasgupta

Doctoral Dissertations

Quantum computing's potential is immense, promising super-polynomial reductions in execution time, energy use, and memory requirements compared to classical computers. This technology has the power to revolutionize scientific applications such as simulating many-body quantum systems for molecular structure understanding, factorization of large integers, enhance machine learning, and in the process, disrupt industries like telecommunications, material science, pharmaceuticals and artificial intelligence. However, quantum computing's potential is curtailed by noise, further complicated by non-stationary noise parameter distributions across time and qubits. This dissertation focuses on the persistent issue of noise in quantum computing, particularly non-stationarity of noise parameters in transmon processors. It …


Towards Structured Planning And Learning At The State Fisheries Agency Scale, Caleb A. Aldridge Dec 2022

Towards Structured Planning And Learning At The State Fisheries Agency Scale, Caleb A. Aldridge

Theses and Dissertations

Inland recreational fisheries has grown philosophically and scientifically to consider economic and sociopolitical aspects (non-biological) in addition to the biological. However, integrating biological and non-biological aspects of inland fisheries has been challenging. Thus, an opportunity exists to develop approaches and tools which operationalize planning and decision-making processes which include biological and non-biological aspects of a fishery. This dissertation expands the idea that a core set of goals and objectives is shared among and within inland fisheries agencies; that many routine operations of inland fisheries managers can be regimented or standardized; and the novel concept that current information and operations can …


Assessing The Influence Of Health Policy And Population Mobility On Covid-19 Spread In Arkansas, Tayden Barretto May 2022

Assessing The Influence Of Health Policy And Population Mobility On Covid-19 Spread In Arkansas, Tayden Barretto

Industrial Engineering Undergraduate Honors Theses

The outbreak of COVID-19 has created a major crisis across the world since its start in 2019, and its influence on every realm of society is undeniable. Globally, more than 500 million cases have been recorded since March 2020, with almost 6 million deaths. In the wake of this crisis, many governments and health organizations have taken steps and precautions to mitigate its spread. These steps involve public mandates of information, reducing frequency of personal contact, and use of masks to minimize the risk of transmission. Current access to mobility data released from Google detailing population movements has provided a …


A Transdisciplinary Analysis Of Just Transition Pathways To 100% Renewable Electricity, Adewale Aremu Adesanya Jan 2021

A Transdisciplinary Analysis Of Just Transition Pathways To 100% Renewable Electricity, Adewale Aremu Adesanya

Dissertations, Master's Theses and Master's Reports

The transition to using clean, affordable, and reliable electrical energy is critical for enhancing human opportunities and capabilities. In the United States, many states and localities are engaging in this transition despite the lack of ambitious federal policy support. This research builds on the theoretical framework of the multilevel perspective (MLP) of sociotechnical transitions as well as the concept of energy justice to investigate potential pathways to 100 percent renewable energy (RE) for electricity provision in the U.S. This research seeks to answer the question: what are the technical, policy, and perceptual pathways, barriers, and opportunities for just transition to …


Developing Leading And Lagging Indicators To Enhance Equipment Reliability In A Lean System, Dhanush Agara Mallesh Dec 2017

Developing Leading And Lagging Indicators To Enhance Equipment Reliability In A Lean System, Dhanush Agara Mallesh

Masters Theses

With increasing complexity in equipment, the failure rates are becoming a critical metric due to the unplanned maintenance in a production environment. Unplanned maintenance in manufacturing process is created issues with downtimes and decreasing the reliability of equipment. Failures in equipment have resulted in the loss of revenue to organizations encouraging maintenance practitioners to analyze ways to change unplanned to planned maintenance. Efficient failure prediction models are being developed to learn about the failures in advance. With this information, failures predicted can reduce the downtimes in the system and improve the throughput.

The goal of this thesis is to predict …


Modelling Supercomputer Maintenance Interrupts: Maintenance Policy Recommendations, Jagadish Cherukuri Aug 2015

Modelling Supercomputer Maintenance Interrupts: Maintenance Policy Recommendations, Jagadish Cherukuri

Masters Theses

A supercomputer is a repairable system with large number of compute nodes interconnected to work in harmony to achieve superior computational performance. Reliability of such a complex system depends on an effective maintenance strategy that involves both emergency and preventive maintenance. This thesis analyzes the maintenance records of four supercomputers operational at The National Institute of Computational Science located at Oak Ridge National Laboratory. We propose to use the generalized proportional intensities model (GPIM) to model the maintenance interrupts as it can capture both the reliability parameters and maintenance parameters and allows the inclusion of both emergency and preventive maintenance. …


Choice And Optimization Of Forecasting Models For Container Port Throughput, Qingcheng Xue Aug 2007

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

World Maritime University Dissertations

No abstract provided.


Optimization Of A Multi-Echelon Repair System Via Generalized Pattern Search With Ranking And Selection: A Computational Study, Derek D. Tharaldson Mar 2006

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 …


Theater-Level Stochastic Air-To-Air Engagement Modeling Via Event Occurrence Networks Using Piecewise Polynomial Approximation, David R. Denhard Sep 2001

Theater-Level Stochastic Air-To-Air Engagement Modeling Via Event Occurrence Networks Using Piecewise Polynomial Approximation, David R. Denhard

Theses and Dissertations

This dissertation investigates a stochastic network formulation termed an event occurrence network (EON). EONs are graphical representations of the superposition of several terminating counting processes. An EON arc represents the occurrence of an event from a group of (sequential) events before the occurrence of events from other event groupings. Events between groups occur independently, but events within a group occur sequentially. A set of arcs leaving a node is a set of competing events, which are probabilistically resolved by order relations. An important EON metric is the probability of being at a particular node or set of nodes at time …


Comparing Traditional Statistical Models With Neural Network Models: The Case Of The Relation Of Human Performance Factors To The Outcomes Of Military Combat, William Oliver Hedgepeth Jan 1995

Comparing Traditional Statistical Models With Neural Network Models: The Case Of The Relation Of Human Performance Factors To The Outcomes Of Military Combat, William Oliver Hedgepeth

Engineering Management & Systems Engineering Theses & Dissertations

Statistics and neural networks are analytical methods used to learn about observed experience. Both the statistician and neural network researcher develop and analyze data sets, draw relevant conclusions, and validate the conclusions. They also share in the challenge of creating accurate predictions of future events with noisy data.

Both analytical methods are investigated. This is accomplished by examining the veridicality of both with real system data. The real system used in this project is a database of 400 years of historical military combat. The relationships among the variables represented in this database are recognized as being hypercomplex and nonlinear.

The …