Operations Research, Systems Engineering and Industrial Engineering Commons^™

How Can The Adoption Of Biodegradable Packaging In The Beverage Industry Specifically Contribute To Reducing Single-Use Plastic Waste, And What Regulatory Or Cost-Related Challenges Hinder Its Widespread Implementation In Developing Countries?, Rebecca Aba Gaisie

2025 Awards for Excellence in Student Research and Creative Activity - Documents

This research investigates the potential of biodegradable packaging to reduce single-use plastic waste in the beverage industry and explores the regulatory and cost-related barriers to its adoption in developing countries. The beverage sector is a major contributor to global plastic pollution, and biodegradable alternatives offer a promising path toward sustainability. Using a mixed-methods approach, this study combines qualitative interviews with industry experts and case studies of businesses implementing biodegradable solutions, alongside quantitative survey data from 100 manufacturers and 200 consumers across Africa, Asia, and Latin America. Findings reveal that while biodegradable packaging significantly reduces plastic waste and appeals to environmentally …

Neural Network-Based Renewal Reward Theory (Rrt) For Optimal Maintenance Scheduling, Samiksha Aryal, Abhijit Gosavi, Susan L. Murray

Miners Solving for Tomorrow Research Conference

No abstract provided.

Sources Of Tensions In Ai Adoption For Organ Procurement Organizations, Amaneh Babaee, Grace Hall, Daniel Burton Shank, Casey I. Canfield

Miners Solving for Tomorrow Research Conference

No abstract provided.

How Do Human And Ai Gender Bias Interact In Hiring Decisions?, Eyuel Getahun, Daniel Burton Shank, Casey I. Canfield, Jessica L. Cundiff, Jenny Davis, Celia Freed

Miners Solving for Tomorrow Research Conference

No abstract provided.

Predicting Baseball Game Wins With Machine Learning, Alexandar Djidjev, Nathan Hellwege

Miners Solving for Tomorrow Research Conference

No abstract provided.

Supply Chain Carbon Finance Indexing With Generative Ai And Advanced Data Analytics Techniques, Pratyush Kumar Patro, Enoch Quaye, Adolf Acquaye, Raja Jayaraman, Khaled Salah

Industrial Engineering: Faculty & Staff Publications

No abstract provided.

Approximations And Bounds For Optimal Controls Via Finite Fourier Series, Gabriel Nicolosi, Terry Friesz, Christopher Griffin

Engineering Management and Systems Engineering Faculty Research & Creative Works

This work considers the problem of approximating initial condition and time-dependent optimal control and trajectory surfaces using multivariable finite Fourier series. A modified Augmented Lagrangian algorithm for translating the optimal control problem into an unconstrained optimization one is proposed. A quadratic control problem in the context of Newtonian mechanics is solved to demonstrate the proposed algorithm and various computational results are presented. Use of automatic differentiation is explored to circumvent the elaborated gradient computation in the first-order optimization procedure. Furthermore, mean square error bounds are derived for the case of one and two-dimensional Fourier series approximations, suggesting a general bound …

A Sysml V2 Implementation Of A Traceability And Verification Metamodel For “-Ilities”, Pacifique Munezero

Engineering Management & Systems Engineering Theses & Dissertations

Multidisciplinary knowledge and exchange of information are two of the most important aspects of complex system design within the Model-Based Systems Engineering (MBSE) domain. The next generation of systems modeling language, SysML v2, is being developed to improve the precision, expressiveness, interoperability, consistency, integration of the language concepts relative to SysML v1, and the implementation and maturation of MBSE approaches. This research focuses on using SysML v2 to model structured notations for -ilities, referred to as non-functional requirements (NFRs), to address how they can be treated with the same rigor as functional requirements and mapped directly and explicitly from the …

A Theoretical Framework For Examination Of Context In Complex System Governance, Meggan M. Schoenberg

Engineering Management & Systems Engineering Theses & Dissertations

“A complex system’s identity and viability are directly related and affected by its context. It is important to identify, monitor, and manage (or mitigate risk) system contextual elements” (Keating C. B. et al., 2022, p. 209). Despite this importance, there is very limited research and literature on complex systems context. This research seeks to expand our understanding of complex system context and improve our ability to govern complex technology development programs effectively. The ability to analyze complex systems and their problems is necessary for this improvement.

A “clear understanding of the specific complex system context is fundamental to the process …

Network Analysis Of Sociotechnical Systems, Siva Kadiresan

Engineering Management & Systems Engineering Theses & Dissertations

Sociotechnical networks have become integral frameworks in the accomplishment of organizational objectives by increasingly diverse, cross-functional, and technology-enabled modern teams. In cross-disciplinary teamwork, multiple mediating and moderating factors appear to lend context to the effects of team diversity faultlines on team outcomes. In the several decades of research into teamwork from a network perspective, there has been a paucity of empirical studies that examine how team transition processes and cross-disciplinary connections influence the impact of faultlines on team performance. This study investigates the association among perceived teamwork effectiveness, transition processes, cross-functional team connections, and faultlines in the context of sociotechnical …

On The Provenance Of Software Systems: Automating Software Traceability With Knowledge Graph And Large Language Model Synergy, Tyler Procko

Doctoral Dissertations and Master's Theses

The present dissertation delineates a system that enables those engaged in software development to automatically generate and maintain project life cycle provenance. All projects are implemented and made manifest with the development of artifacts, e.g., papers, code files, etc. Tools exist to accelerate artifact creation, but little focus is paid to the processes that produce them. In terms of Ontology, or, from Ancient Greek, the study of being, the two most basic entities in reality are Continuant and Occurrent, or, roughly, “Artifact” and “Process”. This dissertation posits that for any created artifact, its process of creation, i.e., its life …

On Generalization Across Environments In Multi-Objective Reinforcement Learning, Jayden Jing Xiang Teoh, Pradeep Varakantham, Peter Vamplew

Research Collection School Of Computing and Information Systems

No abstract provided.

Dual Operation Aggregation Graph Neural Networks For Solving Flexible Job-Shop Scheduling Problem With Reinforcement Learning, Peng Zhao, You Zhou, Di Wang, Zhiguang Cao, Yubin Xiao, Xuan Wu, Yuanshu Li, Hongjia Liu, Wei Du, Yuan Jiang, Liupu Wang

Research Collection School Of Computing and Information Systems

With the widespread adoption of Internet Protocol (IP) communication technology and web-based platforms, cloud manufacturing has become a significant hallmark of Industry 4.0. Integrating graph algorithms into these web-enabled environments is crucial as they facilitate the representation and analysis of complex relationships in manufacturing processes, enabling efficient decision-making and adaptability in dynamic environments. As a key scheduling problem in cloud manufacturing, the flexible job-shop scheduling problem (FJSP) finds extensive applications in real-world scenarios. However, traditional FJSP-solving methods struggle to meet the efficiency and adaptability demands of cloud manufacturing due to generalization issues and excessive computational time, while reinforcement learning-based methods …

Learning-Guided Bi-Objective Evolutionary Optimization For Green Municipal Waste Collection Vehicle Routing, Shubing Liao, Yixin Xu, Yunyun Niu, Zhiguang Cao

Research Collection School Of Computing and Information Systems

Waste management has emerged as a critical issue in modern society, where vehicles are scheduled to visit multiple locations for waste collection and transport. This study focuses on a key problem in waste management: route optimization of waste collection vehicles, and formulate it as a bi-objective vehicle routing problem with stochastic demand (VRPSD), aiming to minimizing both total costs and carbon emissions. Although previous studies have significantly advanced our understanding of solving similar problems, the lack of real-world data and limited problem-solving capabilities still restrict the practical applicability of existing methods. To bridge this research gap, this study designed a …

Leveraging Blockchain And Machine Learning To Promote Child Labor-Free Sustainable Development, Ahmad Musamih, Abduraouf Hassan, Khaled Salah, Raja Jayaraman, Mohammed Omar, Ibrar Yaqoob

Industrial Engineering: Faculty & Staff Publications

Child labor has been on the rise in recent years, which necessitates improved identification and reporting mechanisms. Current labor management systems, which are often manual or article-based, lack traceability, audit, privacy, security, and trust features. This leads to challenges in detecting and reporting violations, particularly in large or remote areas. The persistence of this issue undermines the achievement of Sustainable Development Goals (SDGs) and highlights the important role of Corporate Social Responsibility (CSR) in addressing this challenge. Our article proposes a solution combining machine learning and blockchain to automate child labor detection and ensure traceable, auditable, private, and secure reporting. …

Modeling And Characterization Of On-Orbit Servicing Architectures For Efficient Mission Planning, Samantha Q. Vi Tang

Theses and Dissertations

As space-based systems become increasingly critical to global infrastructure, efficient satellite maintenance and resource management have become essential to ensuring operational longevity. On-orbit servicing has emerged as a key strategy for extending satellite lifespans, mitigating space debris accumulation, and enhancing the cost effectiveness of space operations. This study presents a comprehensive mixed-integer programming (MIP) model to optimize servicer task assignments and routing while minimizing propellant consumption. The model captures the operational complexities of servicing a network of satellites across multiple orbits by incorporating realistic constraints, such as fuel limitations and task completion time windows. Sensitivity analysis allows mission planners to …

Ohio Dot Automated Driving System Deployment Project Findings, Ben Ritchey

Purdue Road School

Attendees will gain a comprehensive understanding of the findings from the OhioDOT Automated Driving Systems (ADS) Deployment project of tractor semi-trailers and Ford transit vans operating on Ohio public roads using Level 2/3 technology. The tractors used truck platooning technology and were operated by a motor carrier in revenue service. The passenger vans operated in three project designated routes using HD maps and were operated by project team members.

Fine-Grained Traffic Flow Inference Model Based On Dynamic Back Projection Network, Ming Xu, Guangyao Qi, Geqi Qi

Journal of System Simulation

Abstract: To solve the problem of large errors in the inference results of existing fine-grained urban flow inference models in complex traffic areas, a fine-grained traffic flow inference model based on dynamic back-projection network is proposed. The multi-dimensional interaction between the input coarse-grained traffic flow and external factors is calculated, and the interaction results are dynamically and adaptively fused with the coarse-grained traffic flow, so that the features can interact and adjust each other to assist model reasoning. Combining deep convolution and self-attention mechanism to learn local information and global information, and improve the understanding of input data by subsequent …

Enhancement Of Hardware-In-Loop Simulation Ability For Homing Guidance Through Adaptive Field-Of-View Method, Shizheng Wan, Yu Cheng, Xu Zhang, Xuwei Fan

Journal of System Simulation

Abstract: Considering homing guidance test in the hardware-in-loop simulation, commands of flight simulator and antenna array are likely to exceed their ranges when the target vehicle maneuvers with a large cross range. To solve this problem, the adaptive field-of-view method is proposed to enhance simulation ability in laboratory. Inflight aircraft attitudes and missile-target line-of-sight angles are chosen as state parameters, and the optimal performance function can be established with maximum servo angle of both flight simulator and antenna array. Gradient descent algorithm is applied to acquire the optimal bias angles between the laboratory coordinate system and the launch inertial coordinate …

Research On Pedestrian Avoidance Strategy For Agv Based On Deep Reinforcement Learning, He Wang, Jianing Xu, Guangyu Yan

Journal of System Simulation

Abstract: To ensure the safety and comfort of pedestrians during Automated Guided Vehicle (AGV) obstacle avoidance in smart factory environments, a deep reinforcement learning-based end-to-end obstacle avoidance method is proposed. The YOLOv8 module is introduced to extract pedestrian pose information, and a visual-based state space is designed. A reinforcement learning mechanism is formulated based on personal space theory, penalizing AGV behaviors such as entering pedestrian comfort space and collisions. A virtual simulation system is constructed, utilizing PPO algorithm along with LSTM network layer for obstacle avoidance strategy training and simulation experiments. Simulation results indicate that this obstacle avoidance strategy, under …