Operations Research, Systems Engineering and Industrial Engineering Commons^™

Utilization Of Integer Programming For Scheduling Maintenance At Nuclear Power Plants, Timothy Gallacher

Doctoral Dissertations

This thesis develops a thought that naturally explores three specific motifs for solving the complexities of scheduling maintenance at Nuclear Power Plants (NPP). The first chapter of this paper will develop the initial thought around creating a schedule for a given work week, including all the various constraints inherent to this problem. Such constraints include but are not limited to personnel availability, allowable component out-of-service time, and the Plant Risk Assessment. The objective function being to minimize the total cost of worker’s compensation for that given week.

The second chapter addresses the question of whether this simple schedule can be …

Exact Models, Heuristics, And Supervised Learning Approaches For Vehicle Routing Problems, Zefeng Lyu

Doctoral Dissertations

This dissertation presents contributions to the field of vehicle routing problems by utilizing exact methods, heuristic approaches, and the integration of machine learning with traditional algorithms. The research is organized into three main chapters, each dedicated to a specific routing problem and a unique methodology. The first chapter addresses the Pickup and Delivery Problem with Transshipments and Time Windows, a variant that permits product transfers between vehicles to enhance logistics flexibility and reduce costs. To solve this problem, we propose an efficient mixed-integer linear programming model that has been shown to outperform existing ones. The second chapter discusses a practical …

Physics-Augmented Modeling And Optimization Of Complex Systems: Healthcare Applications, Jianxin Xie

Doctoral Dissertations

The rapid advances in sensing technology have created a data-rich environment that tremendously

benefits predictive modeling and decision-making for complex systems. Harnessing

the full potential of this complexly-structured sensing data requires the development of

novel and reliable analytical models and tools for system informatics. Such advancements in

sensing present unprecedented opportunities to investigate system dynamics and optimize

decision-making processes for smart health. Nevertheless, sensing data is typically

characterized by high dimensionality and intricate structures. To fully unlock the potential of

this data, we significantly rely on innovative analytical methods and tools that can effectively

process information.

The objective of this …

Scheduling Problem With Drying Requirements, Machine Eligibility Restrictions, Setup Times, And Assembly Requirements For An Injection Molding Facility, Ashley Owens

Doctoral Dissertations

Previous research only focused on an unrelated parallel machine scheduling problem with setup and processing resources. However, some manufacturing environments, such as plastic injection molding, need different sequential and parallel processes before the facility can process jobs in the machines. For example, some raw materials are hygroscopic, and a dryer must remove moisture before being processed in the injection molding machine. These dryers are portrayed as parallel machines. The job rather than the machine determines the drying time. Once the drying stage is complete and the raw materials are transferred to the actual machines to run jobs, the scheduling problem …

Improving Mobility And Safety In Traditional And Intelligent Transportation Systems Using Computational And Mathematical Modeling, Shahrbanoo Rezaei

Doctoral Dissertations

In traditional transportation systems, park-and-ride (P&R) facilities have been introduced to mitigate the congestion problems and improve mobility. This study in the second chapter, develops a framework that integrates a demand model and an optimization model to study the optimal placement of P&R facilities. The results suggest that the optimal placement of P&R facilities has the potential to improve network performance, and reduce emission and vehicle kilometer traveled. In intelligent transportation systems, autonomous vehicles are expected to bring smart mobility to transportation systems, reduce traffic congestion, and improve safety of drivers and passengers by eliminating human errors. The safe operation …

A Study Of The Effect Of Machine Parameters On Defects Produced In Eos Additive Manufacturing Builds, Tina White Malone

Doctoral Dissertations

⁵Additive Manufacturing (AM) is defined in the American Society for Testing and Materials (ASTM) standard F2792 as “a process of joining materials to make objects from 3D model data, usually layer upon layer, as opposed to subtractive manufacturing methodologies. It provides an advanced method for building complex geometries and parts for high performance with a significant cost savings. ⁵⁵It’s advantages include the reduced need for tools and molds commonly used in manufacturing, a large reduction in wasted material, much shorter manufacturing cycles for the building of hardware, and its uniquely inherent ability to produce much more complex shapes. …

Monitoring Additive Manufacturing Machine Health, Jeremy Hale

Doctoral Dissertations

Additive manufacturing (AM) allows the production of parts and goods with many benefits over more conventional manufacturing methods. AM permits more geometrically complex designs, custom and low-volume production runs, and the flexibility to produce a wide variety of parts on a single machine with reduced pre-production cost and time requirements. However, it can be difficult to determine the condition, or health, of an AM machine since complex designs can increase the variability of part quality. With fewer parts produced, destructive testing is less desirable and statistical methods of tracking part quality may be less informative. Combined with the relatively more …

Smart Warehousing Implementaion And Education Of Supply Chain Management Leaders, David Quintanilla

Doctoral Dissertations

Paper #1 Overview

Businesses have to adapt to new challenges and technologies in the marketplace which influence warehousing. In order to support this growth, Industry 4.0 technologies have been implemented along the value chain to optimize their organizations and production processes; however, there are still gaps for warehousing research for Industry 4.0. We present four pillars¾location strategy, infrastructure/design, data management, and advanced planning and control¾ as a framework for businesses to use for their adaptation into smart warehousing. In particular, this framework will guide companies in their logistics journey into Industry 4.0. Industry experts and senior logistics professionals were interviewed …

Exploiting Symmetry In Linear And Integer Linear Programming, Ethan Jedidiah Deakins

Doctoral Dissertations

This thesis explores two algorithmic approaches for exploiting symmetries in linear and integer linear programs. The first is orbital crossover, a novel method of crossover designed to exploit symmetry in linear programs. Symmetry has long been considered a curse in combinatorial optimization problems, but significant progress has been made. Up until recently, symmetry exploitation in linear programs was not worth the upfront cost of symmetry detection. However, recent results involving a generalization of symmetries, equitable partitions, has made the upfront cost much more manageable.

The motivation for orbital crossover is that many highly symmetric integer linear programs exist, and …

Mitigating Space Industry Supply Chain Risk Thru Risk-Based Analysis, Jennifer S. Cooper

Doctoral Dissertations

Using risk-based analysis to consider supply chain disruptions and uncertainty along with potential mitigation strategies in the early stages of space industry projects can be used avoid schedule delays, cost overruns, and lead to successful project outcomes.

Space industry projects, especially launch vehicles, are complicated assemblies of high-technology and specialized components. Components are engineered, procured, manufactured, and assembled for specific missions or projects, unlike make-to-stock manufacturing where assemblies are produced at a mass production rate for customers to choose off the shelf or lot, like automobiles.

The supply chain for a space industry project is a large, complicated web where …

A Novel Approach To Orbital Debris Mitigation, Timothy S. Turk

Doctoral Dissertations

Since mankind launched the first satellite into orbit in 1957, we have been inadvertently, yet deliberately, creating an environment in space that may ultimately lead to the end of our space exploration. Space debris, more specifically, orbital debris is a growing problem that must be dealt with sooner, rather than later. Several ideas have been developed to address the complex problem of orbital debris mitigation.

This research will investigate the possibility of removing orbital debris from the Low Earth Orbit (LEO) regime by using a metaheuristic algorithm to maximize collection of debris resulting from the February 2009 on-orbit collision of …

Optimizing Strategic Planning With Long-Term Sequential Decision Making Under Uncertainty: A Decomposition Approach, Zeyu Liu

Doctoral Dissertations

The operations research literature has seen decision-making methods at both strategic and operational levels, where high-level strategic plans are first devised, followed by long-term policies that guide future day-to-day operations under uncertainties. Current literature studies such problems on a case-by-case basis, without a unified approach. In this study, we investigate the joint optimization of strategic and operational decisions from a methodological perspective, by proposing a generic two-stage long-term strategic stochastic decision-making (LSSD) framework, in which the first stage models strategic decisions with linear programming (LP), and the second stage models operational decisions with Markov decision processes (MDP). The joint optimization …

Carbon Footprint And Cost Minimization For Grid Systems Through Day-Ahead Order And Battery Size Optimization, Omid Pourkhalili

Doctoral Dissertations

We modeled the problem of peak hours day-ahead order for smart grid companies integrating renewable energy and power storage systems. This results in optimizing day-ahead order, battery storage size, and consequently lowering the use of fossil fuels and emissions. The utility-scale power storage can balance the difference between the day-ahead forecasts and real-time consumer demand through energy arbitrage and transmission deferral for peaking capacity. We define system parameters and their associated costs and run a suggested algorithm to minimize the grid operating cost by optimizing day-ahead order amount and battery storage capacity. The model is designed to prioritize and take …

Optimization Methods For Day Ahead Unit Commitment, Jonathan David Schrock

Doctoral Dissertations

This work examines a variety of optimization techniques to better solve the day ahead unit commitment problem. The first method looks at the impact of almost identical generators on the problem and how to exploit that fact for computational gain. The second work seeks to improve the fidelity of the problem by better modeling the impact of pumped storage hydropower. Lastly, the relationship between the length of the planning horizon and the quality of the solutions is investigated.

Defect Detection For Additive Manufacturing With Machine Learning And Markov Decision Process, Rui Li

Doctoral Dissertations

Additive Manufacturing (AM) is a quickly evolving manufacturing technique in recent years. One of the most essential steps is the quality control of it. This involves the defect detection of the products, which is one of the bottlenecks that affects the high quality of AM products. One promising solution to this problem is to detect the defects in-situ and make decisions on the fly. We adopted Machine Learning (ML) algorithms for defect detection and develop a Markov Decision Process (MDP) model to make decisions for AM process. Our main purpose is to save costs and time through early termination or …

Identifying An Optimization Technique For Maker Usage To Address Covid-19 Supply Shortfalls, Michael J. Wilson

Doctoral Dissertations

Fused Deposition Modeling (FDM) can be purchased for under five hundred dollars. The availability of these inexpensive systems has created a large hobbyist (or maker) community. For makers, FDM printing is used numerous uses.

With the onset of the COVID-19 pandemic, the needs for Personal Protective Equipment (PPE) skyrocketed. COVID-19 mitigation strategies such as social distancing, businesses closures, and shipping delays created significant supply shortfalls. The maker community stepped in to fill gaps in PPE supplies.

In the case of 3DP, optimization remains the domain of commercial entities. Optimization is, at best, ad-hoc for makers. With the need to PPE …

Forecasting Nigeria's Electricity Demand And Energy Efficiency Potential Under Climate Uncertainty, Olawale Olabisi

Doctoral Dissertations

The increasing population and socio-economic growth of Nigeria, coupled with the current, unmet electricity demand, requires the need for power supply facilities expansion. Of all Nigeria’s electricity consumption by sector, the residential sector is the largest and growing at a very fast rate. To meet this growing demand, an accurate estimation of the demand into the future that will guide policy makers to adequately plan for the expansion of electricity supply and distribution, and energy efficiency standards and labeling must be made. To achieve this, a residential electricity demand forecast model that can correctly predict future demand and guide the …

Improving Reinforcement Learning Techniques For Medical Decision Making, Matthew Baucum

Doctoral Dissertations

Reinforcement learning (RL) is a powerful tool for developing personalized treatment regimens from healthcare data. In RL, an agent samples experiences from an environment (such as a model of patient health) to learn a policy that maximizes long-term reward. This dissertation proposes methodological and practical developments in the application of RL to treatment planning problems.

First, we develop a novel time series model for simulating patient health states from observed clinical data. We use a generative neural network architecture that learns a direct mapping between distributions over clinical measurements at adjacent time points. We show that this model produces realistic …

Automated Warehouse Systems: A Guideline For Future Research, Wenquan Dong

Doctoral Dissertations

This study aims to provide a comprehensive tool for the selection, design, and operation of automated warehouse systems considering multiple automated storage and retrieval system (AS/RS) options as well as different constraints and requirements from various business scenarios.

We first model the retrieval task scheduling problem in crane-based 3D AS/RS with shuttle-based depth movement mechanisms. We prove the problem is NP-hard and find an optimality condition to facilitate the development of an efficient heuristic. The heuristic demonstrates an advantage in terms of solving time and solution quality over the genetic algorithms and the other two algorithms taken from literature. Numerical …

Optimal Communication Structures For Concurrent Computing, Andrii Berdnikov

Doctoral Dissertations

This research focuses on communicative solvers that run concurrently and exchange information to improve performance. This “team of solvers” enables individual algorithms to communicate information regarding their progress and intermediate solutions, and allows them to synchronize memory structures with more “successful” counterparts. The result is that fewer nodes spend computational resources on “struggling” processes. The research is focused on optimization of communication structures that maximize algorithmic efficiency using the theoretical framework of Markov chains. Existing research addressing communication between the cooperative solvers on parallel systems lacks generality: Most studies consider a limited number of communication topologies and strategies, while the …

Supplier Ranking System And Its Effect On The Reliability Of The Supply Chain, Farshad Rabib

Doctoral Dissertations

Today, due to the growing use of social media and an increase in the number of

A HITS with a solution in PageRank (Massimo, 2011) sharing their opinions globally, customers can review products and services in many novel ways. However, since most reviewers lack in-depth technical knowledge, the true picture concerning product quality remains unclear. Furthermore, although product defects may come from the supplier side, making it responsible for repair cost, it is ultimately the manufacturer whose name is damaged when such defects are revealed. In this context, we need to revisit the cost vs. quality equations. Observations of customer …

A Model For Sustaining New Technology Based On Government Incentives, Girish Upreti

Doctoral Dissertations

The diffusion of new technology that provides environmental benefits may require government incentives for a duration of time, especially when the technology is expensive. The Center of Systems Research and Education (CASRE) model is developed that analyzes the impact of incentives in sustaining new technologies to allow their social acceptance. The CASRE model includes both demand and supply variables associated with incentive policy to sustain new technology. The key to market dissemination and sustainability is the Investment Tax Credit (ITC) levels provided by the government. The level of ITC is based on the current cost to the customer and the …

Model For Prioritization Of High Variation Elements In Discrete Production Systems, Bharadwaj Venkatesan

Doctoral Dissertations

The complexity of the modern manufacturing enterprise has led companies to look for techniques and methodologies for improving production performance. Lean manufacturing techniques have been applied in the US with varying degrees of success, and Theory of Constraints (TOC) has been used to emphasize the flow of production and identify performance improvement projects. One aspect of manufacturing for which there has been limited academic or industrial research till date is the impact of variation on production performance and the identification of improvement projects based on variation. This thesis develops a methodology to incorporate random and simultaneous occurrence of variability in …

Exploring A Semi-Virtual Reality System Impacting Learning Curves Of College Students, Hongbiao Yang

Doctoral Dissertations

Virtual reality (VR) is a trending technology used in a broad range of fields including education and has become one of the most promising directions for educators. In this research, the investigation focuses on how the semi-immersive VR application can be used for educational purposes by exploring the VR factors and the interactions between these factors. A theoretical learning framework is also proposed to offer an explanation for the beneficial effects of education brought by VR at a high level.

This research consists of three parts. First, this research will introduce the development of Walk-in-Place Learning System (WIPLS), a semi-immersive …

Electricity And Fuel Consumption In A Lean Energy Supply Chain, Mostafa Ghafoorivarzaneh

Doctoral Dissertations

Human activities are the main sources of environmental pollution. Awareness about this fact, motivated us to make changes in different paradigms of our lives including industrial or personal activities. Environmental activities assumed to have conflict with financial objectives, in this study we try to align business requirements with environmental concerns.

Among all human activities, generating energy has the most negative impact on the environment. The major part of the generated energy will be consumed in transportation and industrial demand which makes them the most effective targets for the reduction of greenhouse gas emission. In a lean environment, small batch sizes …

Integrating The Cost Of Quality Into Multi-Products Multi-Components Supply Chain Network Design, Waleed Abdussalam Gueir

Doctoral Dissertations

More than ever before the success of a company heavily depends on its supply chain and how efficient the network. A supply chain needs to be configured in such a manner as to minimize cost while still maintaining a good quality level to satisfy the end user and to be efficient, designing for the network and the whole chain is important. Including the cost of quality into the process of designing the network can be rewording and revealing. In this research the concept of cost of quality as a performance measure was integrated into the supply chain network designing process …

Forecasting Employee Turnover In Large Organizations, Xiaojuan Zhu

Doctoral Dissertations

Researchers and human resource departments have focused on employee turnover for decades. This study developed a methodology forecasting employee turnover at organizational and departmental levels to shorten lead time for hiring employees. Various time series modeling techniques were used to identify optimal models for effective employee-turnover prediction based on a large U.S organization's 11-year monthly turnover data. A dynamic regression model with additive trend, seasonality, interventions, and a very important economic indicator efficiently predicted turnover. Another turnover model predicted both retirement and quitting, including early retirement incentives, demographics, and external economic indicators using the Cox proportional hazard model. A variety …

High Reliability Organizational Suggestions To Reduce The Risk Of Hospital-Associated Infections, Sandra Catrice Affare

Doctoral Dissertations

Over 1.7 million hospital-associated infections (HAIs), resulting in 99,000 deaths, occur each year in the United States. HAIs are defined as infections that occur within 48 hours of hospital admission without evidence of the infection being present or incubating at the time of admission. HAIs are a major concern to the medical community due to the potential loss of life and high costs. Healthcare providers should be accountable for reducing the rates of HAIs and society needs to hold them accountable for the safe implementation and outcomes of the services they provide.

A high-reliability organization (HRO) is commonly described as …

Empirical Analysis To Investigate The Influence Of Cultural Dimensions On Risk-Taking Behavior Among Hispanic And Non-Hispanic Construction Workers In United States, Kaveri Ajit Thakur

Doctoral Dissertations

The focus of this research was to investigate the influence of cultural dimensions on risk-taking behavior among construction workers. Following a comprehensive literature review, a conceptual model was presented to evaluate `Intended Behavior in Risky Situations' in construction work environment. While the differences in risk-taking behaviors is generally acknowledged, the influence of culture is overlooked very easily. A total of 94 responses were collected from construction sites in the Knoxville Tennessee area by means of a questionnaire based on the conceptual model factors. The final sample consisted of 89 responses was evaluated using Partial lease Square - Structural Equation Modeling. …

Prognostic Algorithm Development For Plant Monitoring And Maintenance Planning, Them Hill Bui

Doctoral Dissertations

The economic goals in a typical industrial plant are to improve product quality, maximize equipment up-time, reliability, and availability, and minimize spare part inventories and maintenance costs. Modern facilities are comprised of thousands of subsystems with critical unique components. Simple components and more complex engineering systems alike are typically engineered to perform satisfactorily. Their lives can be predicted under normal operation runtime. It should be the same with chronological time lapse from the moment of installation. However, their ages accelerate faster than chronological time lapse if they are operated under unfavorable working conditions, making their remaining life predictions likely not …