Operations Research, Systems Engineering and Industrial Engineering Commons^™

Improving Young Driver Perceptions Of Vulnerable Road Users Through A Persuasive Intervention, Shashank Mehrotra

Doctoral Dissertations

Vulnerable road users (VRUs), including bicyclists, pedestrians, and road users of other modalities, are at a higher risk of collision with young drivers when a complex traffic situation presents itself. Past research has established the importance of young drivers’ perceptions about VRUs that would encourage safe behavior. This research designed and evaluated a novel persuasive intervention that can help improve the perceptions of young drivers while they interact with VRUs. The study identified young drivers’ perceptions towards VRUs who have been licensed in the past 12 to 18 months through structured interviews. Based on these findings, an interactive intervention was …

Advances And Applications In High-Dimensional Heuristic Optimization, Samuel Alexander Vanfossan

Doctoral Dissertations

“Applicable to most real-world decision scenarios, multiobjective optimization is an area of multicriteria decision-making that seeks to simultaneously optimize two or more conflicting objectives. In contrast to single-objective scenarios, nontrivial multiobjective optimization problems are characterized by a set of Pareto optimal solutions wherein no solution unanimously optimizes all objectives. Evolutionary algorithms have emerged as a standard approach to determine a set of these Pareto optimal solutions, from which a decision-maker can select a vetted alternative. While easy to implement and having demonstrated great efficacy, these evolutionary approaches have been criticized for their runtime complexity when dealing with many alternatives 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 …

Modeling Portfolios Of Low Carbon Energy Generation Under Deep Uncertainty, Franklyn Kanyako

Doctoral Dissertations

In the 2015 Paris Agreement, nearly every country pledge through the Nationally Determined Contributions (NDCs) increased adoption of low carbon energy technologies in their energy system. However, allocating investments to different low carbon energy technologies under rising demand for energy and budget constraints, uncertain technical change in these technologies involves maneuvering significant uncertainties among experts, models, and decision-makers. We examine the interactions of low carbon energy sources (LCES) under the condition of deep uncertainty. Deep uncertainty directly impacts the understanding of the role of low carbon energy technologies in climate change mitigation and how much R&D investment should be allocated …

Enabling Declarative And Scalable Prescriptive Analytics In Relational Data, Matteo Brucato

Doctoral Dissertations

Constrained optimization problems are at the heart of significant applications in a broad range of domains, including finance, transportation, manufacturing, and healthcare. They are often found at the final step of business analytics, namely prescriptive analytics, to allow businesses to transform a rich understanding of data, typically provided by advanced predictive models, into actionable decisions. Modeling and solving these problems has relied on application-specific solutions, which are often complex, error-prone, and do not generalize. Our goal is to create a domain-independent, declarative approach, supported and powered by the system where the data relevant to these problems typically resides: the database. …

Extracellular Polymeric Substances In Oxygenic Photogranules: Investigation Of Their Role In Photogranulation In A Hydrostatic Environment, Wenye Camilla Kuo-Dahab

Doctoral Dissertations

The purpose of this dissertation was to assess the critical role of extracellular polymeric substances (EPS) in the photogranulation of activated sludge, in a hydrostatic environment. The first section evaluates the fate and dynamics of different fractions of EPS in sludge-based photogranulation under hydrostatic conditions. The study shows that during the transformation of activated sludge into a photogranular biomass, sludge’s base-extractable proteins selectively degrade. Strong correlations between base-extracted proteins and the growth of chlorophyll a and chlorophyll a/b ratio suggest that the bioavailability of this organic nitrogen is linked with selection and enrichment of filamentous cyanobacteria under hydrostatic conditions. The …

Factors Affecting Drivers’ Off-Road Glance Behavior While Interacting With In-Vehicle Voice Interfaces – Insights From A Secondary Data Analysis, Fangda Zhang

Doctoral Dissertations

Given the prevalence of in-vehicle technologies and the critical role of visual attention plays in driving safety, this dissertation work aimed to fill the research gap that 1) little was known about the visual demands associated with a driver engaging with in-vehicle voice interfaces; 2) the concurrent effect of interacting with in-vehicle voice interfaces and other commonly discussed individual-level factors has barely been targeted. This research work was a secondary data analysis based on a large-scale field experiment wherein 144 participants had been recruited and driven a test vehicle while performing a series of tasks using voice-based interfaces. Pre- and …

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 …

Quality And Productivity Improvements In Additive Manufacturing, Huseyin Kose

Doctoral Dissertations

Additive manufacturing (AM) is a relatively new manufacturing technology compared to the traditional manufacturing methods. Even though AM processes have many advantages, they also have a series of challenges that need to be addressed to adapt this technology for a wide range of applications and mass production.

AM faces a number of challenges, including the absence of methods/models for determining whether AM is the best manufacturing process for a given part. The first study of this thesis proposes a framework for choosing specific AM processes by considering the complexity level of a part. It has been proven that the method …

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 …

Optimization Of Islanded Utility-Microgrids After Natural Disasters, Rodney Kizito

Doctoral Dissertations

Natural disasters can cause widespread disturbances/power outages within distribution networks and hinder a utility’s ability to provide uninterrupted power supply to the critical public buildings (e.g., hospitals, grocery stores, fire, police and gas stations) within the utility’s serviced region. Backup generators, which are typically relied on during power interruptions, have limited capacities and have been reported to experience failures during usage. Microgrids, defined as localized power grids that incorporate distributed generators (DGs) and energy storage systems (ESSs) to allow them to operate independent of the main grid (i.e., island mode), can help utilities provide disaster relief power supply to critical …

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 …

Models, Theoretical Properties, And Solution Approaches For Stochastic Programming With Endogenous Uncertainty, Tanveer Hossain Bhuiyan

Doctoral Dissertations

In a typical optimization problem, uncertainty does not depend on the decisions being made in the optimization routine. But, in many application areas, decisions affect underlying uncertainty (endogenous uncertainty), either altering the probability distributions or the timing at which the uncertainty is resolved. Stochastic programming is a widely used method in optimization under uncertainty. Though plenty of research exists on stochastic programming where decisions affect the timing at which uncertainty is resolved, much less work has been done on stochastic programming where decisions alter probability distributions of uncertain parameters. Therefore, we propose methodologies for the latter category of optimization under …

Human Fatigue Predictions In Complex Aviation Crew Operational Impact Conditions, Suresh Rangan

Doctoral Dissertations

In this last decade, several regulatory frameworks across the world in all modes of transportation had brought fatigue and its risk management in operations to the forefront. Of all transportation modes air travel has been the safest means of transportation. Still as part of continuous improvement efforts, regulators are insisting the operators to adopt strong fatigue science and its foundational principles to reinforce safety risk assessment and management. Fatigue risk management is a data driven system that finds a realistic balance between safety and productivity in an organization. This work discusses the effects of mathematical modeling of fatigue and its …

The Implementation Of Energy Sharing Using A System Of Systems Approach, Julia Morgan

Doctoral Dissertations

"There is an increasing demand for renewable energy and consumers need more procurement options to meet their needs. Energy sharing provides a peer-to-peer (P2P) marketplace where prosumer electricity is redistributed to fellow energy-sharing community participants. This redistribution of prosumer electricity provides consumers with additional electricity suppliers, while also decreasing the load on the utility company. Though significant progress has been made regarding research and implementation of energy sharing, there is still room for growth when evaluating energy-sharing communities and defining appropriate community coordination based on end-user needs. The first contribution in this work identified nine characteristics of energy-sharing communities as …

A Fuzzy Clustering Methodology To Analyze Interfaces And Assess Integration Risks In Large-Scale Systems, Josh Henry Goldschmid

Doctoral Dissertations

“Interface analysis and integration risk assessment for a large-scale, complex system is a difficult systems engineering task, but critical to the success of engineering systems with extraordinary capabilities. When dealing with large-scale systems there is little time for data gathering and often the analysis can be overwhelmed by unknowns and sometimes important factors are not measurable because of the complexities of the interconnections within the system. This research examines the significance of interface analysis and management, identifies weaknesses in literature on risk assessment for a complex system, and exploits the benefits of soft computing approaches in the interface analysis in …

Sensor Data Based Adaptive Models For Assembly Worker Training In Cyber Manufacturing, Md. Al-Amin

Doctoral Dissertations

“Production innovations are occurring faster than ever leading conventional production systems towards cyber manufacturing. Manufacturing workers thus need to frequently learn new methods and skills. In fast-changing, largely uncertain production systems, manufacturers with the ability to comprehend workers’ behavior and assess their operational performance in near real-time will achieve better performance than peers. Recognizing worker actions in near real-time while performing the assembly can serve this purpose. However, reliably recognizing the assembly actions performed by the workers is challenging, because the actions for assembly are complex and workers are not only heterogeneous but sensitive to the variation of the work …

Infrastructure Systems Modeling Using Data Visualization And Trend Extraction, Jacob Marshal Hale

Doctoral Dissertations

“Current infrastructure systems modeling literature lacks frameworks that integrate data visualization and trend extraction needed for complex systems decision making and planning. Critical infrastructures such as transportation and energy systems contain interdependencies that cannot be properly characterized without considering data visualization and trend extraction.

This dissertation presents two case analyses to showcase the effectiveness and improvements that can be made using these techniques. Case one examines flood management and mitigation of disruption impacts using geospatial characteristics as part of data visualization. Case two incorporates trend analysis and sustainability assessment into energy portfolio transitions.

Four distinct contributions are made in this …

Establishing Links Between Safety Culture, Climate, Behaviors, And Outcomes Of Long-Haul Truck Drivers, Carlton Washburn

Doctoral Dissertations

“This research examines the safety relationships between safety culture, safety influences, safety climate, and safety outcomes for long-haul truck drivers. The relationships focus on the intersection of the electronic logging device (ELD) technology, regulations, and truck drivers that fall into the lone-worker category. Truck drivers were interviewed to understand their beliefs, attitudes, practices, values, and behavior patterns aligned with the phase in of the ELD system. Large truck crashes during the same time period were analyzed to understand associations. Outcomes included both a safety culture and climate were established for long-haul truck drivers. Both positive and negative safety behaviors were …

Improving Drivers’ Behaviour When Partial Driving Automation Fails, Yalda Ebadi

Doctoral Dissertations

With the advent of automated vehicle systems, the role of drivers has changed to a more supervisory role. However, it is known that all vehicles with Level 2 (L2) systems have a very specific operational design domain (ODD) and can only function on limited conditions. Hence, it is important for drivers to perceive the situations properly and regain the control from the L2 system when needed. As suggested by past research, designing an informative interface could help drivers in their new supervision and intervention role while driving with L2 vehicles by providing feedback to drivers when hazards or event that …

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 …

Robust And Sustainable Energy Pathways To Reach Mexico’S Climate Goals, Rodrigo Mercado Fernandez

Doctoral Dissertations

As countries set climate change goals for adaptation and mitigation efforts, there are many questions regarding to how to reach these targets. These efforts will necessitate the transition of our electricity infrastructure from relying on conventional electricity generation technologies including natural gas, coal and oil, to clean energy generation with renewables. Through the three essays presented in this dissertation, we explore various pathways of development for the electricity system to reach long term climate change goals. We are interested in identifying: Is there a unique optimal development option or are there various? How do different mixes of electricity generation technologies …

Predicting Complex System Behavior Using Hybrid Modeling And Computational Intelligence, Vinayaka Gude

Doctoral Dissertations

“Modeling and prediction of complex systems is a challenging problem due to the sub-system interactions and dependencies. This research examines combining various computational intelligence algorithms and modeling techniques to provide insights into these complex processes and allow for better decision making. This hybrid methodology provided additional capabilities to analyze and predict the overall system behavior where a single model cannot be used to understand the complex problem. The systems analyzed here are flooding events and fetal health care. The impact of floods on road infrastructure is investigated using graph theory, agent-based traffic simulation, and Long Short-Term Memory deep learning to …

Development Of A Modeling Algorithm To Predict Lean Implementation Success, Richard Charles Barclay

Doctoral Dissertations

”Lean has become a common term and goal in organizations throughout the world. The approach of eliminating waste and continuous improvement may seem simple on the surface but can be more complex when it comes to implementation. Some firms implement lean with great success, getting complete organizational buy-in and realizing the efficiencies foundational to lean. Other organizations struggle to implement lean. Never able to get the buy-in or traction needed to really institute the sort of cultural change that is often needed to implement change. It would be beneficial to have a tool that organizations could use to assess their …

Enabling Flexibility Through Strategic Management Of Complex Engineering Systems, Walter Louis Barnes Ii

Doctoral Dissertations

”Flexibility is a highly desired attribute of many systems operating in changing or uncertain conditions. It is a common theme in complex systems to identify where flexibility is generated within a system and how to model the processes needed to maintain and sustain flexibility. The key research question that is addressed is: how do we create a new definition of workforce flexibility within a human-technology-artificial intelligence environment?

Workforce flexibility is the management of organizational labor capacities and capabilities in operational environments using a broad and diffuse set of tools and approaches to mitigate system imbalances caused by uncertainties or changes. …

Integrating Resilience Into Military Infrastructure Mission Assurance Assessments And Decision Making, John Richards

Doctoral Dissertations

“This research created the Mission Assurance Resilience Matrix, a decision framework that integrates existing infrastructure assessment methods with emerging resilience research to model resilience under uncertainty as part of a detailed infrastructure management system. This framework enables military decision makers to easily visualize deficiencies in infrastructure resilience and assess where to most efficiently allocate resources. This research further extends results by including modules on training and education as a component of the scope of work.

There are three significant contributions of this research. The first identifies the gaps of how and where modeling under uncertainty, infrastructure systems management, and resilient …

Computational Model For Neural Architecture Search, Ram Deepak Gottapu

Doctoral Dissertations

"A long-standing goal in Deep Learning (DL) research is to design efficient architectures for a given dataset that are both accurate and computationally inexpensive. At present, designing deep learning architectures for a real-world application requires both human expertise and considerable effort as they are either handcrafted by careful experimentation or modified from a handful of existing models. This method is inefficient as the process of architecture design is highly time-consuming and computationally expensive.

The research presents an approach to automate the process of deep learning architecture design through a modeling procedure. In particular, it first introduces a framework that treats …

Microgrid Design, Control, And Performance Evaluation For Sustainable Energy Management In Manufacturing, Md. Monirul Islam

Doctoral Dissertations

"This research studies the capacity sizing, control strategies, and performance evaluation of the microgrids with hybrid renewable sources for manufacturing end use customers towards a distributed sustainable energy system paradigm. Microgrid technology has been widely investigated and applied in commercial and residential sector, while for manufacturers, it has been less explored and utilized. To fill the gap, the dissertation first proposes a cost-effective sizing model to identify the capacities as well as control strategies of the components in microgrids considering a commonly used energy tariff, i.e., Time of Use (TOU). Then, the sizing model is extended by integrating control strategies …

Development Of A System Architecture For The Prediction Of Student Success Using Machine Learning Techniques, Tatiana A. Cardona

Doctoral Dissertations

“ The goals of higher education have evolved through time based on the impact that technology development and industry have on productivity. Nowadays, jobs demand increased technical skills, and the supply of prepared personnel to assume those jobs is insufficient. The system of higher education needs to evaluate their practices to realize the potential of cultivating an educated and technically skilled workforce. Currently, completion rates at universities are too low to accomplish the aim of closing the workforce gap. Recent reports indicate that 40 percent of freshman at four-year public colleges will not graduate, and rates of completion are even …