Operations Research, Systems Engineering and Industrial Engineering Commons^™

Pathways To Efficient And Equitable Solutions For Large-Scale Routing Problems, Abhay Sobhanan

USF Tampa Graduate Theses and Dissertations

This dissertation addresses large-scale optimization problems in transportation emerging from hierarchical decision-making, equitable workload allocation, and innovative routing logistics. It presents three sets of contributions, each detailed in a separate chapter, and offers computational tools and insights to advance both the theory and practice of transportation systems.

The first work introduces a deep learning-enhanced genetic algorithm framework for solving the Hierarchical Vehicle Routing Problems (HVRPs). Traditional optimization approaches to such problems require extensive evaluation of multiple lower-level routing solutions and are computationally intensive. Our innovative method integrates a genetic algorithm with a pretrained graph neural network, which is trained on …

Integrating Risk And Vulnerability: Exploring A Unified Model For Supply Chain Resiliency, William G. Cook

USF Tampa Graduate Theses and Dissertations

The world has entered an era of retreating globalization, mounting geo-political tensions, rising protectionism, and increasing focus on the fragility of complex supply chains. The negative impacts of supply chain disruptions have been increasingly documented since the turn of the century. Given the global scale of recent disruptions, supply chain resiliency has become a national imperative. The Global Financial Crisis, the Covid-19 pandemic, and other major disruptive events demonstrate the active role of government in mitigating damage, the enduring effects of regulation, and the resultant re-evaluation of supply chain strategies by the private and public sectors. In this environment, supply …

A Robust Data-Driven Framework For Artificial Intelligent Systems, Quoc H. Nguyen

USF Tampa Graduate Theses and Dissertations

Artificial Intelligence (AI) systems have demonstrated remarkable performance across various domains. However, their robustness remains a critical concern, particularly in terms of data and model reliability. This dissertation aims to address the challenges associated with building robust AI systems by focusing on two key aspects: data robustness and model robustness. Data robustness poses significant challenges, including data shift, concept shifting, limited and imbalanced datasets, and interoperability issues in IoT systems for data collection. Existing methods fall short in handling dynamic business objectives and evolving data landscapes effectively. To bridge these gaps, we propose an IoT framework that ensures interoperability, seamless …

Routing Problems Through The Lens Of Hybrid Algorithms, Sasan Mahmoudinazlou

USF Tampa Graduate Theses and Dissertations

This dissertation explores novel approaches to address complex combinatorial optimization challenges in transportation and routing scenarios. Three sets of contributions are presented, each encapsulated in a chapter. The first set of contributions introduces a pioneering hybrid genetic algorithm meticulously crafted to address the intricacies of the Traveling Salesman Problem with Drone (TSPD) and the Flying Sidekick Traveling Salesman Problem (FSTSP). These emerging problems involve the strategic use of both ground-based trucks and aerial drones for efficient package delivery. Our algorithm stands out by leveraging sophisticated chromosomes and dynamic programming, allowing for broad exploration by the genetic algorithm and effective exploitation …

Knowledge Integration In Domain-Informed Machine Learning And Multi-Scale Modeling Of Nonlinear Dynamics In Complex Systems, Phat K. Huynh

USF Tampa Graduate Theses and Dissertations

Nonlinear dynamical systems have been extensively used to model various phenomena in the changing world around us, especially in science and engineering fields. Thanks to breakthrough advancements in sensing technologies, an increasingly high volume of multi-modal sensor data has been collected, which enables us gain better insights into complex systems dynamics and build sophisticated data-driven machine-learning-based dynamic models without having the access to the underlying governing equations. However, integrating domain-specific knowledge in machine learning algorithms remains pivotal for various reasons: it promises enhanced predictive accuracy, better model interpretability, and increased generalizability. This dissertation delves into three core research questions, each …

The Aging Workforce: How It Relates To Incident Rates Within A Distribution Warehouse And A Chemical Manufacturing Building, Elisabeth V. Jones

USF Tampa Graduate Theses and Dissertations

Over the past 20 years or so, the average age of the global population has slowly increased. This is due to low birth rates as well as increased life expectancy. With this global population aging, there has also been a shift in the global labor market causing a trend termed the “aging workforce.” However, with the aging workforce comes a new set of issues for the health and safety professional because they create new hazards. This is due mostly because of the body undergoing physical, psychological, and cognitive decline as someone ages which causes decreased capabilities. Thus, the purpose of …

Cyber-Physical Multi-Robot Systems In A Smart Factory: A Networked Ai Agents Approach, Zixiang Nie

USF Tampa Graduate Theses and Dissertations

This dissertation focuses on addressing the technical challenges of non-stationarity in smart factories through the use of cyber-physical AI agents. Industry 4.0 and smart manufacturing with smart factories as a central role, have a growing demand for Just-in-Time (JIT) and on-demand production, as well as mass customization—all while maintaining high productivity, resource efficiency and resilience. This research positions Multi-Robot Systems (MRS)-driven smart factories. The heterogeneous production and transportation robots in an MRS collaborate to form multiple real-time adjusted production flows achieving the flexibility to accommodate such on-demand, mass customization.

However, the implementation of MRS introduces new sets of challenges, including …

Process Automation And Robotics Engineering For Industrial Processing Systems, Drake Stimpson

USF Tampa Graduate Theses and Dissertations

Automation in industrial systems applications has emerged as the fundamental solution for improving quality, production rate, and efficiency of a process. Much of the recent popularity surrounding the transition of processes from manually operated tasks to automated systems can be attributed to the concept of Industry 4.0, which outlines the fundamental guidelines for integrating cyber-physical systems into industrial processes. Due to rapid advancement of technology in robotics and automation as well as the increase in accessibility of resources to this technology, the capability to develop automated systems has become feasible for small-scale enterprise. This work presents a two-part initiative to …

Stochastic Models For Resilience Assessment And Improvement, Weimar Ardila Rueda

USF Tampa Graduate Theses and Dissertations

Resilience refers to the ability of a system to absorb and mitigate the impact of potential disruptions and return to normal operational conditions. The above notion of resilience allows us to distinguish two stages in a system's post-disruption response, the absorptive dimension and the recovery dimension. The absorptive dimension is related to a system's robustness and capacity to mitigate initial loss posterior to a disruption. Meanwhile, the recovery dimension is the system's rapidity to return and reach an acceptable level of functionality after the disruption occurrence.

A social-physical (SP) system's post-disruption response is related to its resilience capacity so building …

Degradation Performance Modeling And Optimal Maintenance Planning Of Deteriorating Critical Infrastructures, Hung Q. Nguyen

USF Tampa Graduate Theses and Dissertations

Serving as the backbone of the nation’s economy, a large and growing number of deteriorating critical infrastructures, such as transportation and water infrastructures, are underperforming, aging, becoming structurally deficient, and must be repaired or replaced. Due to the influence of a variety of factors (e.g., material structure, design, operation, and environmental conditions) at different phases of lifecycle and the costly data acquisition process, field degradation of deteriorating infrastructures is highly uncertain with limited degradation data. The co-location and spatial proximity between many infrastructures, such as road and water infrastructures, further makes them physically and operationally interdependent. The sheer deterioration of …

Computational Methods For Solving The Combinatorial Optimization Problems In Transportation, Xufei Liu

USF Tampa Graduate Theses and Dissertations

This dissertation discusses three transportation problems. The first problem is a bi-level optimization problem that simultaneously optimizes facility locations and network design in hazardous materials transportation. In the upper level, the leader intends to reduce the facility setup cost and the hazmat exposure risk, by choosing facility locations and road segments to close for hazmat transportation. When making such decisions, the leader anticipates the response of the followers who want to minimize the transportation costs. A robust optimization approach with multiplicative uncertain parameters and polyhedral uncertainty sets is applied to deal with the uncertain risk and demand.

The second problem …

Statistical Monitoring The Quality Of Healthcare Services, Yanqing Kuang

USF Tampa Graduate Theses and Dissertations

In today’s healthcare industry, quality of care is a growing focus in the delivery of healthcare. To improve the quality of care in healthcare delivery, many studies focus on the longterm operational decision making to meet the expectations of healthcare providers and users, such as medical resource allocation, bed planning, staff scheduling, etc. These problems are typically parts of long-term operational decision making, however, time is essential in healthcare system. To ensure the adherence to a high quality of care and detect deterioration in real time, the quality of service should be measured over days or hours instead of just …

Theory And Algorithms For Systems Optimization, Vahid Mahmoodian

USF Tampa Graduate Theses and Dissertations

This dissertation presents four sets of contributions in the field of theory and algorithms for system optimization. In the first set, we introduce a simulation optimization method for redistributing bikes in a free-floating bike sharing system. The second set of contributions is a framework for batching queries in large databases to optimize the data retrieval time. The third set includes two branch-and-bound algorithms to solve minimum multiplicative programming problems and one branch-and-bound algorithm to solve the maximum form of the mentioned problems. At last, the fourth set presents an approach to fairlyassign delivery tasks in an outsourcing last-mile delivery system …

Healthcare Data Analytics For Predicting Health Outcomes Of Older Adults And Emergency Responses Of Aged Care Facilities, Nazmus Sakib

USF Tampa Graduate Theses and Dissertations

The United States (US) is experiencing rapid growth in its older adult population, who may suffer from multiple chronic diseases, injuries, and impairments. To meet with the excess demand without compromising the quality of care for older adults, the current aged care systems, such as nursing home systems, will face unprecedented challenges of healthcare resource shortage with rising costs. Accurate prediction of health outcomes of individual older adults will facilitate the aged care professionals to better prioritize healthcare resources for the most at-risk individuals with more focused care and provide more proactive and individualized treatment and care delivery. In addition, …

Analysis And Modeling Of Strategic Interactions In Health Systems To Improve Patient Care Access, Jorge A. Acuña Melo

USF Tampa Graduate Theses and Dissertations

Affordable health care access that provides well-coordinated and high-quality services on time is a goal that governments and health organizations strive for. Regrettably, most countries deal with access problems that affect the population's health, such as long waiting lists for specialized medical services, overcrowding of emergency departments, and high health prices. In the present doctoral dissertation, I model and analyze the strategic interactions that inhabit the health system machinery to uncover possible structural problems that led to the aforementioned issues. The study involves operation research, data science, and game theory techniques to address the health care access predicament.

Each research …

Maximum Multiplicative Programming: Theory, Algorithms, And Applications, Payman Ghasemi Saghand

USF Tampa Graduate Theses and Dissertations

This dissertation presents three different contributions to an important class of optimization problems known as Multiplicative Programs (MPs). The first group of contributions contains the development and analysis of several multi-objective optimization-based based algorithms designed to find the optimal solution of Mixed Integer Linear MPs. As for the second group, the application of a special class of MPs in radiotherapy planning is presented. Finally, in the last group, a new technique for conducting the multiplication process in the objectives of MPs is presented. Using this technique, we introduce a family of novel solution methods that are capable of solving both …

Data-Informed Decision Support To Improve Pediatric And Maternal Care Quality Under Medicaid Managed Care Settings, Hasan Symum

USF Tampa Graduate Theses and Dissertations

Over the last two decades, the United States has spent almost twice as much per person in healthcare compared to most other wealthy countries. However, this higher spending has not necessarily transformed into improved quality of care; According to World Health Organization reports, the US now ranks 39th for child health and wellbeing and worst in maternal care among developed nations. In terms of proportion of preventable hospital visits, low-risk cesarean sections, and avoidable maternal morbidity/death, the U.S. is among the highest compared with the peer nations. The prevalence of these adverse outcomes in pediatric and obstetric care is particularly …

Strategies For Achieving The United States Health System's Quadruple Aim By Enhancing The Primary Care Level, Jennifer L. Mendoza-Alonzo

USF Tampa Graduate Theses and Dissertations

The quadruple aim is an approach to optimize the performance of the health system in the United States and consists of four dimensions. The main objective is to improve the population's health, followed by reducing cost, improving patients' experience, and increasing providers' satisfaction. In the present doctoral dissertation, I explore three strategies that help accomplish the quadruple aim at the primary care level. The analysis combines data science and operation research principles to address health system engineering questions.

Each strategy proposed in this document emphasizes one objective more than another; however, all of them in conjunction serve to attain the …

Heterogeneous Performance Modeling With Applications In Healthcare And Reliability Engineering, Xuxue Sun

USF Tampa Graduate Theses and Dissertations

In both health systems engineering and reliability engineering, individual units, such as patients and product units, often exhibit highly heterogeneous performance due to the influences of various observed individual characteristics and unobserved/unknown factors. Successful modeling of the heterogeneous performance of individual units is of great importance. It will not only facilitate the identification and quantification of influencing factors for improving performance of individual units, but also improve prediction accuracy of their future performance. This will further facilitate better decisions, such as cost-effective and adaptive healthcare resource planning decision, and proactive maintenance policy at reduced cost. However, due to the highly …

The Utilization Of Shared Energy Storage In Energy Systems: Design, Modeling And Optimization, Rui Dai

USF Tampa Graduate Theses and Dissertations

Energy storage (ES) plays a significant role in modern smart grids and energy systems. With the advances of ES technologies, efficiently applying ES to energy systems has become the bottleneck for achieving the benefits of ES. The traditional approach of utilizing ES is the so-called distributed framework in which there is a separate ES for each individual user. Due to the inherent limits in the distributed framework such as cost inefficiency and space limitations, many studies have promoted to utilize a shared ES in energy systems to further exploit the potentials of ES. However, current studies always focus on maximizing …

Efficient Neural Architecture Search With Multiobjective Evolutionary Optimization, Maria Gabriela Baldeón Calisto

USF Tampa Graduate Theses and Dissertations

Deep neural networks have become very successful at solving many complex tasks such as image classification, image segmentation, and speech recognition. These models are composed of multiple layers that have the capacity to learn increasingly higher-level features, without prior handcrafted specifications. However, the success of a deep neural network relies on finding the proper configuration for the task in hand. Given the vast number of hyperparameters and the massive search space, manually designing or fine-tuning deep learning architectures requires extensive knowledge, time, and computational resources.

There is a growing interest in developing methods that automatically design a neural network´s architecture, …

Using Optimization Methods For Solving Problems In Sustainable Urban Mobility And Conservation Planning, Zulqarnain Haider

USF Tampa Graduate Theses and Dissertations

This dissertation considers three separate optimization problems related to sustainable urban and environmental systems. The first problem relates to the nightly relocation and recharging operations for Free-floating electric vehicle sharing (FFEVS) systems. Such operations involve a crew of drivers to move the shared electric vehicles (EVs), and a fleet of shuttles to transport those drivers. Mixed integer programs are used to model the relocation and recharging operations. Two approaches are devised: sequential and synchronized approaches. In the sequential approach, the movement of EVs is first decided, then the routing of shuttles and drivers is determined. In the synchronized approach, all …

Identification Of Patterns And Disruptions In Ambient Sensor Data From Private Homes, Yan Wang

USF Tampa Graduate Theses and Dissertations

The world’s population is rapidly aging and the increasing demand for home and health care services from this aging population brings unprecedented challenges to the economy and society. Ambient-assisted smart homes, residences equipped with ambient sensors to monitor the resident’s daily activities in a continuous and unobtrusive way, present great potential to manage the growing care service needs of this older population segment, and enable them to age-in-place.

Despite growing research, using ambient sensor data from private homes to monitor daily activities, health and wellness still faces significant challenges. To study ambient sensor data from private homes where annotated data …

Game Theory Approaches For Transportation Problems, Mahdi Takalloo

USF Tampa Graduate Theses and Dissertations

This dissertation considers three separate game theory problems in transportation. In the first problem, a combinatorial auction market has been proposed for fractional ownership of autonomous vehicles. The proposed combinatorial auction has two unique features. First, the items are continuous time slots defined by bidders and second, the spatial information of bidders has been incorporated so that sharing becomes a viable plan. A conflict-based formulation of the winner determination problem has been proposed, for which an effective solution approach based on a heuristic and a maximal-clique based relaxation has been presented. The second part of the dissertation examines a pessimistic …

Some Recent Advances In Design Of Bayesian Binomial Reliability Demonstration Tests, Suiyao Chen

USF Tampa Graduate Theses and Dissertations

Reliability demonstration test (RDT) is one of important reliability assurance activities to demonstrate products' quality over time. Binomial RDT (BRDT) is one class of RDTs with appealing features, such as less failure monitoring efforts and fewer reliability modeling assumptions. Integrating with Bayesian method further allows prior knowledge incorporation for potential test sample size reduction. However, conventional designs often assume the binary failure states (i.e., success and failure) and consider a single objective of minimizing the testing cost with limited planning horizon. In this dissertation, a series of RDT designs are proposed and studied by advancing the conventional Bayesian BRDT designs …

On The Convergence Of Transportation And Power Systems In Smart And Connected Communities, Kevin A. Melendez

USF Tampa Graduate Theses and Dissertations

Even though the total number of light-duty vehicles in the U.S. is expected to increase by 2030, total fuel consumption is expected to significantly decrease in the same timeframe. This contradictory behavior is in part explained by the increasing utilization of electricity as the primary source of energy in the transportation sector. Due to its potential to decrease dependency on fossil fuels, electric transportation has become a promising approach to alleviate the increasing environmental crisis. Passenger car markets are expected to experience a flood of new Electric vehicles (EVs) in the next few years. EVs are considered effective resources to …

Algorithms For Multi-Objective Mixed Integer Programming Problems, Alvaro Miguel Sierra Altamiranda

USF Tampa Graduate Theses and Dissertations

This thesis presents a total of 3 groups of contributions related to multi-objective optimization. The first group includes the development of a new algorithm and an open-source user-friendly package for optimization over the efficient set for bi-objective mixed integer linear programs. The second group includes an application of a special case of optimization over the efficient on conservation planning problems modeled with modern portfolio theory. Finally, the third group presents a machine learning framework to enhance criterion space search algorithms for multi-objective binary linear programming.

In the first group of contributions, this thesis presents the first (criterion space search) algorithm …

Prioritizing Strategic Cyberspace Lethality, Andrew J. Schoka

Military Cyber Affairs

The primary concern of United States national security policy, as detailed in the 2018 National Defense Strategy, has shifted from asymmetrical counter-insurgency operations to countering inter-state strategic competition by rogue regimes and revisionist powers. This doctrinal shift has prompted an increased emphasis on military lethality, particularly in strategic-level cyberspace operations intended to counter open challenges to the global security environment and United States preeminence. Drawing from the theory of constraints in industrial engineering and Bayesian search theory in operations research, this paper identifies the key organizational constraints that hinder the lethality of the Department of Defense’s strategic-level cyberspace operations units …

Essays On Time Series And Machine Learning Techniques For Risk Management, Michael Kotarinos

USF Tampa Graduate Theses and Dissertations

The Capital Asset Pricing Model combined with the Sharpe ratio is a standard method for choosing assets for selection in a portfolio. However, this method has many structural issues and was designed for a time when high dimensional computing was in its infancy. An alternative to these methods using a mix of Multi-Level Time Series Clustering, the MACBETH algorithm and traditional time series techniques was constructed that minimized data loss and allow for customized portfolio construction for investors with different risk profiles and specialized investment needs. It was shown that these methods are adaptable to cloud computing environments and allow …

Routing And Designing Networks For Two Transportation Problems, Liu Su

USF Tampa Graduate Theses and Dissertations

Routing and designing are essential for transportation networks. With effective routing and designing policies, transportation networks can work safely and efficiently. There are two transportation problems: hazardous materials (hazmat) transportation and warehouse logistics. This dissertation addresses the routing of networks for both problems. For hazmat transportation, the routing can be regulated via network design. Due to catastrophic consequences of potential accidents in hazmat transportation, a risk-averse approach for routing is necessary. In this dissertation, we consider spectral risk measures, for risk-averse hazmat routing. In addition, we introduce a network design problem to select a set of closed road segments for …