Improving Transfer Portal Decision-Making Through A Microsoft Excel Optimization Model,
2026
Bowling Green State University
Improving Transfer Portal Decision-Making Through A Microsoft Excel Optimization Model, Peyton Steffes
Honors Projects
The creation of the transfer portal has increased the mobility of collegiate athletes, giving players the autonomy to switch teams throughout their career. As a result, the roster development process has become more complex, as coaches are tasked with the challenge of recruiting from the transfer portal, which involves an extensive decision-making process. Coaches not only have to evaluate a substantial pool of players, but they also must consider the following constraints they are under: scholarship budget, roster spots available, and positional needs. To simplify this decision-making process, this analysis includes the results of a Microsoft Excel data optimization model …
Optimization Of Vehicle Mix For Three-And Four-Wheel Passenger Transportation System In Nigeria,
2026
University of Ibadan, Ibadan, Nigeria
Optimization Of Vehicle Mix For Three-And Four-Wheel Passenger Transportation System In Nigeria, Omotunde A. Muyiwa, Hamid A. Jimoh, Kolawole T. Oriolowo
Tanzania Journal of Engineering and Technology (TJET)
Efficient transportation systems are essential for reducing passengers waiting times in densely populated areas. However, there is a dearth of information on the optimization of vehicle mix for three-and four-wheel transportation systems in Nigeria. The present study was designed to optimize the vehicle mix for three-and four-wheel passenger transportation to improve transportation efficiency. Twenty purposively selected vehicles were observed, while a queuing model (M/M/s) was used to determine passenger arrival rates during different periods (morning, afternoon, and evening). An integer linear programming model was developed to minimize passenger waiting times. Data on vehicle types, capacities, travel cycles, and average passenger …
Ai-Scm Cmm: A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management,
2026
Dakota State University
Ai-Scm Cmm: A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management, Lordt Becklines, Omar F. El-Gayar, Patti Brooks, Insu Park
Annual Research Symposium
Artificial intelligence is increasingly deployed in supply chain management, yet many organizations struggle to align adoption efforts with process readiness, data quality, governance, and workforce capabilities, and they still lack validated supply chain specific roadmap for assessing readiness, sequencing investments, and reducing implementation risk. This study develops and evaluates a Capability Maturity Model for Artificial Intelligence Integration in Supply Chain Management to address that gap. Using a design science research approach, the study synthesizes prior literature and practitioner knowledge to define maturity dimensions, capability indicators, and staged progression levels for AI integration in supply chain contexts. The artifact and assessment …
Analogy2kg: An Automatic Pipeline For Deriving Knowledge Graphs From Long-Text Analogies,
2026
Sensors Directorate, Air Force Research Laboratory
Analogy2kg: An Automatic Pipeline For Deriving Knowledge Graphs From Long-Text Analogies, Kara Combs, Lance E. Champagne, Bruce A. Cox, Christine M. Schubert Kabban, Trevor Bihl, Grace Lemming
Faculty Publications
Analogical reasoning is an increasingly popular, lightweight solution to enable large language model (LLM)-level reasoning without computational complexity. Still, it has yet to be adopted due to its reliance on strictly hand-formatted data. Therefore, we propose Analogy2KG (“Analogy to Knowledge Graph”), as an automatic pipeline that transforms text into a KG format via a fine-tuned version of information extraction (IE) algorithms for long-text analogies. The need to verify that the complex underlying analogical structure of the data is maintained was done via paired samples tests in the creation and validation of this pipeline. Graph density was used to evaluate the …
Multi-Objective Optimization Of Waste Incineration For Minimal Carbon Monoxide And Sulfur Dioxide Emission And Rate Maximization: A Case Study Of Mbezi, Mkuranga-Pwani, Tanzania,
2026
Department of Mechanical and Industrial Engineering, College of Engineering and Technology, University of Dar es Salaam, Dar es Salaam, Tanzania, P. O. Box 35131 Dar es Salaam, Tanzania
Multi-Objective Optimization Of Waste Incineration For Minimal Carbon Monoxide And Sulfur Dioxide Emission And Rate Maximization: A Case Study Of Mbezi, Mkuranga-Pwani, Tanzania, Grangay M. Nyanghura, Enock W. Nshama
Tanzania Journal of Science
Incineration is widely employed for hazardous waste disposal, but results in harmful flue gas emissions. This study optimizes a double-chamber incineration process to reduce sulfur dioxide (SO2) and carbon monoxide (CO) emissions while maximizing the incineration rate. The effects of waste mass, primary chamber temperature (PT), and secondary chamber temperature (ST) were analyzed using a full factorial design of 27 experiments. ANOVA revealed that mass had the greatest impact on emissions and incineration time, ST had a moderate effect, and PT had little influence. Regression analysis provided models for incineration time, CO, and SO2 emissions. Single-objective optimization using sequential quadratic …
A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management,
2026
Dakota State University
A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management, Lordt Becklines
Dissertations
Artificial Intelligence (AI) is transforming Supply Chain Management (SCM), yet many organizations struggle to assess their readiness for AI adoption and to understand how AI capabilities develop across maturity stages. This dissertation addresses this gap by developing a Capability Maturity Model (CMM) for AI integration in SCM, grounded in Organizational Information Processing Theory (OIPT), the Resource-Based View, and related capability frameworks. The model provides a structured approach for evaluating an organization's information-processing requirements, resource configurations, and alignment needed for effective AI-enabled supply chain operations.
Using a design science research approach, the AI-SCM CMM and its associated assessment instrument were derived …
Optimal Placement Of Electric Vehicle Chargers: A Mixed-Integer Linear Programming Model,
2026
University of New Hampshire, Durham
Optimal Placement Of Electric Vehicle Chargers: A Mixed-Integer Linear Programming Model, Joubin Zahiri Khameneh, Emmanuel Fagbenle
Faculty Publications
Electric vehicle adoption is growing, but New Hampshire lags in public charging infrastructure, especially in rural areas. This gap increases range anxiety and economic inefficiencies. In this study, we developed a mixed-integer linear programming (MILP) model to optimally locate new electric vehicle chargers statewide, maximizing coverage and equity under budget constraints. The model includes geographic coverage requirements, population-weighted equity, capacity limits, and a $28 million budget. Moreover, the model recommends 855 Level 2 chargers and 149 Direct Current Fast Chargers (DCFCs) across 247 ZIP Codes, nearly doubling public charging capacity and achieving 98.8% coverage within defined service radii. The plan …
Bridging Mission And Execution: Integrating Participatory Design In Early-Phase Mission Engineering For Stakeholder Alignment And Mission Clarity,
2026
Old Dominion University
Bridging Mission And Execution: Integrating Participatory Design In Early-Phase Mission Engineering For Stakeholder Alignment And Mission Clarity, Rafi Soule
Knowledge and Creativity Expo
This research examines mission framing during the early phase of Mission Engineering. Stakeholder interpretations diverge under ambiguity. Interoperability constraints are often not surfaced early. These conditions reduce mission clarity and weaken mission-to-system mapping readiness. The study integrates a participatory design-inspired, artifact-first workflow with RAG-enabled retrieval from a closed corpus to support evidence-grounded reasoning and traceable citations.
Phase 1 uses an online survey to establish baseline patterns in practice (N = 86). Shared understanding is positively associated with mission clarity (r = 0.60, p < 0.001). Phase 2 uses a time-bounded comparative workshop with two conditions. Expert reviewers rate mission statement quality higher for the participatory design condition (mean 3.5) than the traditional condition (mean 2.8). Technical feasibility ratings are similar across conditions. Phase 3 demonstrates RAG-enabled, closed-corpus, retrieval-supported traceability using the Referencer tool. It is reported as a proof-of-concept for evidence-grounded rationale and auditability, and as a pathway …
Gpu-Accelerated Biased Random-Key Genetic Algorithms: Framework Optimization And Llm-Driven Configuration,
2026
University of Rhode Island
Gpu-Accelerated Biased Random-Key Genetic Algorithms: Framework Optimization And Llm-Driven Configuration, Fnu Harishjitu Saseendran
Open Access Master's Theses
This thesis presents two complementary contributions to the field of GPU-accelerated evolutionary metaheuristics for combinatorial optimization, organized in manuscript format.
The first manuscript, “BrkgaCuda 3.0: A Redesigned Multi-GPU Framework for Biased Random-Key Genetic Algorithms,” presents a ground-up architectural redesign of BrkgaCuda 2.0 that enables a true multi-GPU island model for Biased Random-Key Genetic Algorithms (BRKGA). The BRKGA island model evolves multiple semi-independent populations that periodically exchange elite solutions, a structure that maps naturally to multi-GPU parallelism; however, BrkgaCuda 2.0 is confined to a single GPU. BrkgaCuda 3.0 introduces an IslandManager that distributes populations across any number of GPUs, with multiple …
Business Process Redesign For Reducing Undelivered Product Return Losses In E-Commerce – An Explainable Ai Approach,
2026
Indian Institute of Management Tiruchirappalli, India
Business Process Redesign For Reducing Undelivered Product Return Losses In E-Commerce – An Explainable Ai Approach, Venkataraghavan Krishnaswamy, Deepa R, Himanshu Sharma
Journal of International Technology and Information Management
Product returns in e-commerce affect the profitability of the e-tailer. We adopt a two-stage approach to reduce undelivered product returns in an e-commerce firm. First, we develop and compare machine learning techniques—logistic regression, decision trees, Naïve Bayes, random forest, adaptive boosting, gradient boosting, stochastic gradient boosting, and deep neural networks—on their ability to predict undelivered returns. Next, we use explainable methods, such as relative importance and Shapley values, to develop insights from the best-performing machine learning model. Finally, we use these insights and the predictive model to redesign the firm’s order fulfillment and return processes. A Post-implementation evaluation of the …
Online Community Dynamics: An Analysis Using Louvain During Major Sporting Events,
2026
SVKM's NMIMS Mukesh Patel School of Technology Management & Engineering, Mumbai
Online Community Dynamics: An Analysis Using Louvain During Major Sporting Events, Anushka Jaint, Yashodhan Karulkar, Kashish Jindal, Sri Sai Harshita Gadavarthi, Sanya Gulati
Journal of International Technology and Information Management
With the power of social media transforming the way people connect and interact with each other, the dynamics of community formation on platforms such as X during major events are of crucial importance. While social media is an increasingly key driver in determining interactions, little is known about the online influence forming and developing fan communities in high-stakes events. This study looks into the development of user communities for datasets drawn from Kaggle on two of the world’s largest sporting events: the FIFA World Cup 2022, or football, and the T20 World Cup 2022, or cricket, with the aim of …
The Role Of Ict In Enhancing National Logistics Performance And Economic Productivity,
2026
University of Houston, Downtown
The Role Of Ict In Enhancing National Logistics Performance And Economic Productivity, Jin Ho Kim
Journal of International Technology and Information Management
This study sheds light on the transformative impact of Information and Communication Technology (ICT) on national productivity via logistics performance. By distinguishing between mobile and wired Internet speeds, the research demonstrates how these technologies influence logistics performance and, in turn, national productivity across different economic contexts. The findings reveal a nuanced relationship between ICT and logistics performance, with mobile ICT playing a more significant role in developing countries due to its accessibility and cost-effectiveness. In contrast, developed countries benefit from a balanced integration of both mobile and wired ICT. Moreover, the study highlights the mediating role of logistics performance in …
Blockchain As A Digital Coordination Infrastructure For Project Management: A Systematic Review And Integrative Framework,
2026
Dakota State University
Blockchain As A Digital Coordination Infrastructure For Project Management: A Systematic Review And Integrative Framework, Cherie Bakker Noteboom, Sai Neelima Seru, Aravindh Sekar
Journal of International Technology and Information Management
Blockchain technology has gained increasing attention as a digital infrastructure capable of improving transparency, trust, and coordination in complex, multi-organizational project environments. However, existing research on blockchain-enabled project management remains fragmented and industry-focused, providing limited guidance for organizational adoption and integration. This study addresses this gap through a systematic literature review of 29 peer-reviewed studies, following PRISMA guidelines, to examine how blockchain capabilities are incorporated into project management practices across industries and maturity stages.
Grounded in Resource-Based View and Coordination Theory, the analysis employs a feature-to-process mapping approach to link six core blockchain capabilities—decentralization, transparency, immutability, smart contracts, traceability, and …
The Crowdfunding Paradox In Crisis: Rising Funder Demand Vs. Declining Entrepreneur Supply,
2026
James Madison University
The Crowdfunding Paradox In Crisis: Rising Funder Demand Vs. Declining Entrepreneur Supply, Dan Liu, Guangzhi Shang, Cynthia Fan Yang
Journal of International Technology and Information Management
This study investigates how the crowdfunding marketplace responds to major crises, focusing on behavioral shifts among funders and entrepreneurs. Results show a dual impact on platform dynamics. On the demand side, funders become more engaged, with notable increases in the number of backers, average contributions, and total pledge amounts. This heightened activity suggests stronger altruistic motivations, as individuals view crowdfunding as a way to support others during difficult times. On the supply side, however, entrepreneurs act more cautiously, leading to a decline in new project launches. This drop likely reflects increased risk aversion and uncertainty as creators navigate volatile conditions. …
Too Warm To Win Big? Unpacking The Backer Dynamics Behind Female Crowdfunding Success Using A Warmth And Competence Perspective,
2026
James Madison University
Too Warm To Win Big? Unpacking The Backer Dynamics Behind Female Crowdfunding Success Using A Warmth And Competence Perspective, Dan Liu
Journal of International Technology and Information Management
While crowdfunding is often heralded as a democratized funding avenue that empowers women with higher success rates, this study reveals a more nuanced picture of gender dynamics. The Stereotype Content Model suggests that women are often perceived as warmer but less competent. Using a large dataset from Kickstarter, we find that female-led projects can attract more backers, likely due to warmth-driven appeal, but receive smaller average contributions, potentially due to concerns about risk linked to lower perceived competence. However, the total funding raised by female-led campaigns is comparable to that of male-led ones, showing no clear advantage or disadvantage. This …
Simulation Optimization Of Intermodal Freight Transportation Under Disruptions,
2026
West Virginia University
Simulation Optimization Of Intermodal Freight Transportation Under Disruptions, Israt Humayra
Graduate Theses, Dissertations, and Problem Reports (ETD)
Rapid growth in freight transportation in modern supply chains has led to increased operational costs, congestion, and severe environmental impacts, especially greenhouse gas emissions. Combining different modes, such as highway, railway, and waterway, intermodal transportation could thus offer considerable benefit to improve efficiency, sustainability, and resilience. However, most existing planning approaches rely on simplified assumptions, fixed schedules, and average cost estimates, making them less relevant to dealing with real-world uncertainties and disruptions. This study develops a simulation-optimization framework for intermodal freight transportation under disruption. We develop a mixed-integer programming model to represent an intermodal logistics planning framework on a multi-layered …
An Integrated Pull System Framework For Disassembly Industries: Bridging The Supply-Demand Mismatch In Duck Meat Processing,
2026
Northern Illinois University
An Integrated Pull System Framework For Disassembly Industries: Bridging The Supply-Demand Mismatch In Duck Meat Processing, Hongchao Yu
Graduate Research Theses & Dissertations
Disassembly-based production systems, such as duck meat processing, face inherent operational challenges due to one-to-many production structures, short product shelf life, and volatile customer demand. A single carcass must be processed into multiple products at largely fixed biological ratios, while demand varies across products and over time. This supply-demand mismatch frequently leads to simultaneous surplus and shortage, resulting in unstable shipment schedules, excess inventory, and unavoidable waste. Traditional order-driven pull systems typically respond to orders independently and are limited in their ability to coordinate these interrelated effects.
This dissertation develops an integrated pull system framework for perishable disassembly processes, using …
Lean Service System Optimization In U.S. Automotive Maintenance Centers: A Time Study And Simulation-Based Approach To Reducing Service Cycle Time And Increasing Efficiency,
2026
Minnesota State University, Mankato
Lean Service System Optimization In U.S. Automotive Maintenance Centers: A Time Study And Simulation-Based Approach To Reducing Service Cycle Time And Increasing Efficiency, Rakibul Hasan Sarker
All Graduate Theses, Dissertations, and Other Capstone Projects
The primary objective of this study is to measure the current service time at a U.S. automobile service center, with the aim of reducing waste and optimizing service operations through time study and simulation modeling. Inefficiencies in those service centers increase service time and labor costs, reduce service quality, and reduce workshop productivity, thereby increasing customer waiting time. In this study, real-world shop floor data were collected from a single service center, namely Jiffy Lube. Over the course of ten working days, 205 vehicle data points were acquired. Service time, bay time, and overall process time were computed and examined …
Fasttree-Guided Genetic Algorithm For Credit Scoring Feature Selection,
2025
University of Bahrain
Fasttree-Guided Genetic Algorithm For Credit Scoring Feature Selection, Rashed Bahlool, Nabil Hewahi Prof., Youssef Harrath Dr.
Research & Publications
Feature selection is pivotal in enhancing the efficiency of credit scoring predictions, where misclassifications are critical because they can result in financial losses for lenders and exclusion of eligible borrowers. While traditional feature selection methods can improve accuracy and class separation, they often struggle to maintain consistent performance aligned with institutional preferences across datasets of varying size and imbalance. This study introduces a FastTree-Guided Genetic Algorithm (FT-GA) that combines gradient-boosted learning with evolutionary optimization to prioritize class separability and minimize falserisk exposure. In contrast to traditional approaches, FT-GA provides fine-grained search guidance by acknowledging that false positives and false negatives …
The Iron Pyramid: Expanding The Iron Triangle To Integrate Safety As A Fundamental Dimension Of Construction Success,
2025
Clemson University
The Iron Pyramid: Expanding The Iron Triangle To Integrate Safety As A Fundamental Dimension Of Construction Success, Laura Cooley
All Theses
For more than fifty years, construction project success has been judged by staying on schedule, remaining within budget, and completing the planned scope of work—an approach commonly known as the “Iron Triangle” (Barnes, Ph.D., 2006). While these measures are important, they do not capture the full range of factors that determine whether a project truly succeeds.
This study introduces the “Iron Pyramid” (Cooley, 2025), a model that expands the traditional framework by adding a fourth dimension: safety. Safety is understood not simply as regulatory compliance or the absence of injuries, but as a holistic construct encompassing project culture, leadership practices, …
