Operational Research Commons^™

Spatial Markov Equilibrium Models For Taxi Services: Driver Decision, Search Friction, And Locational Pricing, Yanchao Liu

Industrial and Systems Engineering Faculty Research Publications

This paper develops a modeling framework for stochastic multi-agent systems and applies it to equilibrium and pricing analysis in urban taxi markets. Travel demand is represented as a trip network and embedded in a Markov chain that captures both locational and in transit taxi states, with transition dynamics reflecting trip durations, search frictions, spatial competition, and drivers’ perceptions of long-term value. The framework features a parametric Markov chain with endogenous transition probabilities and a behavioral model in which agents’ decisions depend on anticipated long-term rewards. We establish equilibrium existence and examine two locational pricing schemes that align individual incentives with …

Optimization Of Gas Consumption, Cost And Production Rate For Computerized Numerical Control Oxy-Acetylene Flame Cutters, Eustace K. William, Simon I. Marandu, Enock W. Nshama

Tanzania Journal of Science

This study examined the impact of flame cutting parameters (i.e., cutting speed, plate thickness and nozzle diameter) on oxy-acetylene gas consumption, cost and production rate. A full factorial design of experiments was used to generate 27 experiments, which were conducted using a CNC flame cutter. The analysis of variance (ANOVA) method was used to determine significant process parameters, followed by regression analysis using the MINITAB ® software. The technique for order preference by similarity to ideal solutions (TOPSIS) was used to determine the optimal cutting parameters for minimizing the consumption and cost estimation of oxy- acetylene gas and maximizing the …

Innovative Controls For Combustible Particulate Dust In Industrial Refineries, Sadie Dickman

Discovery Day - Daytona Beach

This project entails an extensive analysis of the occupational combustible dust hazard that exists in industrial refineries, including food processing, manufacturing, and metalworking facilities. Based on prior accidents like the 2008 Imperial Sugar and 2017 Didion Milling explosions, combustible dust causes fire and explosion risks that can result in damages, injuries, and fatalities. Through comparison of OSHA regulations, NFPA standards, and accident data, a lack of effective standards regarding training, audits, ventilation, fire prevention, and adequate housekeeping measures were highlighted to be an existing safety gap. The purpose of this study is to propose administrative controls to mandate companies to …

Designing Under Pressure: A Comparative Study Of Ai And Manual Interface Development In A Naval Weapon System Scenario, Tsimur Babakhanau, Noah Clark, Colby Keller, Mary Grace Sorenson, Zoe Tiede

Discovery Day - Daytona Beach

This study implements a detailed naval scenario in which participants acted as operators on a Navy destroyer equipped with a Laser Weapon System (LaWS). Their task was to create a dashboard capable of stopping incoming suicide drone swarms while managing critical laser functions such as thermal constraints, threat prioritization, and adapting to attack dynamics. Poor management could leave the ship vulnerable. AI is increasingly integrated into design methods, fundamentally transforming the process of building user interfaces by compressing hours of work into minutes. Although AI design tools are becoming more common, little is known about how well beginners can use …

Shipboard Fire & Flooding: Evaluating Ai-Assisted Interface Design For Novice Designers, Rachel Phillips, Abigail Threat, Parneet Makkar, Jasmine Cruz, Matthew Skowronek

Discovery Day - Daytona Beach

In naval damage control scenarios, operators in Damage Control Central (DCC) must interpret information from numerous sensors at once to detect hazards such as fire, flooding, or smoke while also maintaining ship stability. Designing interfaces that effectively support these tasks typically requires significant experience in human factors and military design standards. This project investigates whether AI-based design tools can help novice users produce functional interface prototypes more efficiently. Participants were randomly divided into two groups: an experimental group that used an assigned AI tool (Figma Make, Visily, or Claude) to generate and refine interface layouts, and a control group that …

High Tempo Air Operations, Joseph Lipson, Brennan Flanagan, Trevor Sterbens, Brandon Godfrey, Jeremiah Sepich

Discovery Day - Daytona Beach

Aircraft carrier flight decks are one of the most dangerous work environments in the world, where dozens of aircraft must be moved, fueled, and armed within strict time limits. Currently, Flight Deck Handling Officers track aircraft positions using a physical board with wooden pucks that can be knocked out of place or become outdated during fast-moving operations. This study looks at whether using AI tools helps people design a better digital version of this tracking system. Participants with little design experience were randomly selected and then randomly assigned to one of two groups — one that could use AI tools …

Humans Vs. Ai: Comparing Approaches To Disaster Response Interface Design, Kelly Nguyen, Olivia Hartmann, Kailey Hrbek, Madeline Nees, Gabrielle Roth, Emily Silliman

Discovery Day - Daytona Beach

Amphibious emergency support operations involve rapidly changing information, high stress, and significant cognitive demands, which can make decision-making and situation awareness more difficult for operators. When interfaces are poorly designed, they can contribute to issues such as alarm flooding, confusion from incomplete information, and delayed responses, all of which increase operational risk during time-critical disaster situations. This study explores whether using generative AI to assist with interface design will improve performance (output quality and effort) and usability compared to a manual sketch mock-up. Participants were asked to design a dashboard interface to support disaster relief operations following a Category 5 …

Robbed With Permission: Toward A Receiver-Consent Architecture For Trust-Preserving Mobile Money Transactions In Africa, Raphael Amponsah

African Conference on Information Systems and Technology

Mobile money transacted more than USD 2 trillion globally in 2025 across 2.3 billion registered accounts, with Sub-Saharan Africa holding over half of all accounts and two-thirds of transaction value. Between 58 and 72 percent of mobile money fraud on the continent exploits trust rather than technology, yet current security architecture authenticates the sender and merely notifies the receiver, leaving the transaction execution moment structurally unguarded. This paper introduces the Receiver-Consent Transaction Protocol (RCTP), a USSD-native protocol requiring the receiver's active PIN consent on their physical SIM before any credit completes, grounded in Design Science Research with Routine Activity Theory …

C.S.A. Assessment - Tamp Family Health Center Portal, Delante Clark

Graduate Scholarship and Creative Works

This C.A.S. assessment evaluates how the Tampa Family Health Centers website influences userattention, cognitive processing, information accessibility, navigation efficiency, and digital user experience.The assessment examines whether the platform supports intentional engagement and informed decision-making while minimizing cognitive overload, distraction, confusion, and unnecessary attentional demands.

TFHC serves as a healthcare access portal providing appointment scheduling, patient resources, providerinformation, healthcare services, MyChart access, payment services, and community health resources.These functions make attention management and information clarity critical to successful user outcomes.

Bridging Models And Real-World Performance: Capturing Represented, Hidden, And Unrepresented Dynamics In Complex Systems, Dixizi Liu

All Dissertations

Complex systems often depend on adaptive performance that is difficult to capture using structured data or formal models alone. This dissertation asks how predictive modeling, coordination-cost measurement, and simulation can be integrated to better represent the visible, hidden, and unrepresented dynamics that shape real-world system performance.

Sterile Processing Departments (SPDs) provide the empirical context for this work because they support safe and timely surgical care while operating under high workload variability, time pressure, and tight coordination with operating rooms. Hospitals rely on SPDs to clean, assemble, sterilize, and deliver surgical instrument trays so surgeries can start on time and proceed …

Balancing War And Peace In Taekwondo Athlete Development: A Multi-Criteria Coaching Decision Support Framework Using Leadership Scale For Sports And Fuzzy Ahp, King Harold A. Recto, Hazel Jade L. Antonio, Jhyrald Anthony P. Dalida

Electronics, Computer, and Communications Engineering Faculty Publications

Coaching effectiveness is frequently evaluated through competitive outcomes, with the assumption that coaching behaviors directly influence athlete performance. This study examined the relationship between perceived coaching behaviors and individual win percentage among collegiate Taekwondo athletes using the Leadership Scale for Sports (LSS). Descriptive statistics, correlation analysis, and regression analysis were conducted across five coaching dimensions: Training and Instruction, Democratic Behavior, Autocratic Behavior, Social Support, and Positive Feedback. Results showed that none of the coaching dimensions demonstrated a statistically significant relationship with win percentage. Although coaching behaviors did not significantly predict win percentage, the findings suggest that athlete development is shaped …

Drones In Wildfire Airspace Management: Developing A Scalable Framework For Mid-Sized Cities, Victoria Denise Tanner Williamson

Engineering Management & Systems Engineering Theses & Dissertations

Wildfires are becoming increasingly frequent and severe, creating growing risks for mid-sized communities with limited emergency response resources. The January 2025 Los Angeles wildfires—which burned more than 57,000 acres and destroyed over 18,000 structures—underscore the urgent need to strengthen wildfire response strategies through the integration of unmanned aerial systems (UAS) (Hardy, 2025).

This study develops a scalable framework for drone-assisted wildfire response in resource-constrained environments. Using the city of Waynesboro, Virginia, as a case study, the research examines how mid-sized jurisdictions can integrate unmanned aerial vehicles (UAVs) to improve preparedness, response, and recovery. A three-round, mixed-methods Delphi study engages emergency …

Structure Meets Context: A Simulation Study Of Centralized And Decentralized Decision-Making In Complex Environments, Murat Balci

Engineering Management & Systems Engineering Theses & Dissertations

The question of when to centralize or decentralize decision-making authority is a foundational problem in organizational theory and management science. Yet existing research often favors decentralized structures, frequently treating them as universally superior, and provides limited guidance on when centralization may be more effective. Leaning toward decentralization without thoroughly exploring options leaves organizational designers without clear direction under varying environmental conditions. This study addresses that gap by developing and applying a simulation-based framework to evaluate the context-dependent effectiveness of centralized and decentralized decision-making structures.

Drawing on contingency theory and decision science, the study conceptualizes environmental complexity along two dimensions: dynamism …

Improving Cancer Diagnosis And Patient Outcomes With Deep Learning Models, Mariana Arriz-Jorquiera

USF Tampa Graduate Theses and Dissertations

Cancer care depends on timely and reliable decisions, from detection and diagnosis to treatment planning and patient monitoring. These decisions are often made under uncertainty because medical images and healthcare data may be noisy, incomplete, or difficult to interpret. In breast cancer imaging, ultrasound is widely used because it is safe, accessible, and complementary to other imaging modalities. However, variations in image quality, acquisition conditions, and noise can obscure lesion boundaries and texture, affecting human interpretation and artificial intelligence reliability. This dissertation develops deep learning, image-analysis, and optimization methods to improve healthcare decisions under imperfect information. Its primary focus is …

From Shortage To Strategy: Optimizing Scarce Resource Allocation In Healthcare, Daniela Duran Cantarino

USF Tampa Graduate Theses and Dissertations

The allocation of scarce medical resources presents one of the most consequential challenges in health care, requiring decisions that balance equity and efficiency under pervasive uncertainty. This dissertation develops optimization-based frameworks for two critical domains, organ transplantation and emergency medical services, and demonstrates how operations research methods can improve upon current practice along both dimensions simultaneously.

In the domain of deceased-donor kidney allocation, two complementary frameworks are proposed. The first is a bi-objective stochastic optimization model that jointly maximizes post-transplant survival (efficiency) and prioritizes candidates with the highest pre-transplant mortality risk (equity), subject to regional chance constraints on graft failure …

Prediction Of Satellite Temperature During An Orbit Of A Cubesat, Michael Reynolds

Honors Theses

This thesis develops a thermal-simulation strategy for predicting CubeSat component temperatures, applied to Jag-Sat-1, a CubeSat developed at the University of South Alabama and deployed from the International Space Station in 2022. The orbit was reconstructed from two-line element (TLE) data using simplified general perturbations (SGP4) propagation, and spacecraft attitude was recovered from onboard gyroscope measurements. Sunlight, penumbra, and umbra intervals were computed geometrically, and the external radiative environment — direct solar, Earth infrared, and albedo heat fluxes — was modeled using orientation-dependent view factors. These time-varying fluxes drove a transient finite-element thermal simulation of the full satellite geometry in …

Optimizing Escort Strategies For Chokepoint And Littoral Maritime Lanes Using Mixed-Integer Programming, Shantonu Mitra

Graduate Theses and Dissertations

Protecting high-value units (HVUs) while traversing maritime chokepoints under threats is a significant challenge that requires effective planning for allocating limited naval assets (escort ships, detection capabilities, and defensive capabilities). Although the weapon-to-target assignment problem has been previously studied in the literature, the problem of allocating limited naval assets under uncertain threat scenarios remains unexplored. This research develops a two-stage stochastic optimization framework with the objective of maximizing the expected weighted survivability of HVUs across all scenarios. The first-stage decisions include assigning available escorts to HVUs, selecting locations for deploying detection capabilities, and allocating defensive capabilities to each escort prior …

Integrasi Metodologi Hazop Dalam Pengendalian Risiko Dan Keberlanjutan Operasional Pada Unit Pemulihan Urea: Studi Kasus Pada Industri Pupuk, Riny Yolandha Parapat, Arin Nur'aini Putri, Aryasatya Ramadhan Sukresno

National Journal of Occupational Health and Safety

The fertilizer industry is one of the chemical sectors with high-risk potential due to its operational processes involving hazardous materials as well as extreme pressure and temperature conditions. This study aims to identify and analyze hazards in the urea recovery unit using the Hazard and Operability Study (HAZOP) method, while also formulating effective risk control strategies to support the operational sustainability of the plant. The study was conducted directly at a commercial fertilizer plant in West Java using a semi-quantitative approach, which included field observations, review of technical documents such as Process Flow Diagrams (PFD), Piping and Instrumentation Diagrams (P&ID), …

Integrating Production And Repair Operations Through Data Driven Defect Flow Analytics For Yield And Resource Optimization In Pcba Manufacturing, Ali Tahmasebi, Yingge Zhou, Daryl Santos, Sai Srikanth Reddy Kolli, Edward Wong

Systems Science and Industrial Engineering Student Scholarship

In Printed Circuit Board Assembly (PCBA) manufacturing, maintaining a closed loop connection between production and repair operations is critical to improving product quality and operational efficiency. However, in the manufacturing environment that motivated this work, production and repair data are often managed separately, and repair findings are not systematically fed back to production teams, limiting visibility into defect routing patterns and repair workload drivers. This study developed a data-driven framework that integrates production and repair data streams to analyze defect flow and support repair resource planning. The framework applies descriptive statistics, cross tabulations of repair inflow by product/project and repair …

Can Generative Ai Make Farming Decisions? Current Status And Future Pathways: A Case Study In Row Crop Production With Chatgpt, Nipuna Chamara, Yufeng Ge, Joe Luck, Yu Pan, Saleh Taghvaeian, Cory Walters, Christopher Proctor, Daran Rudnick, Daren Redfearn

Department of Agricultural and Biological Systems Engineering: Faculty Publications

The agricultural decision-making process is experience-based, knowledge-dependent, time-sensitive, complex, and driven by historical data. Planting, fertilization, irrigation, and chemigation are key categories in farm decision-making, and currently there is no one-shot decision-support tool that covers all these activities. Generative Artificial Intelligence (AI) models are more advanced than traditional machine learning and deep learning models. These models have been trained on vast amounts of data from the internet, allowing them to accept unstructured data in various forms and generate human-like text, solutions to problems, and scenario predictions. Given this capability, we became interested in exploring the potential of generative AI in …