Operations Research, Systems Engineering and Industrial Engineering Commons^™

Systemic Risk In Financial Networks, Tathagata Banerjee

McKelvey School of Engineering Graduate Student Theses & Dissertations

In this dissertation, I have used the network model based approach to study systemic risk in financial networks. In particular, I have worked on generalized extensions of the Eisenberg--Noe [2001] framework to account for realistic financial situations viz. pricing of corporate debt while accounting for network effects, asset liquidation mechanisms during fire sales, dynamic clearing and impact of contingent payments such as insurance and credit default swaps. First, I present formulas for the valuation of debt and equity of firms in a financial network under comonotonic endowments. I demonstrate that the comonotonic setting provides a lower bound to the price …

Design And Validation Of A Modular Instrument To Measure Torque And Energy Consumption In Industrial Operations, Mary De La Cruz, Ramiro Gonzalez, Jesus A. Gomez, Atilano Mendoza, Javier A. Ortega

Mechanical Engineering Faculty Publications

A modular torque measuring instrument capable of performing tapping torque tests (TTT) according to the ASTM D-5619 standard was designed, developed, and validated. With this new instrument, the performance of different lubricants can be evaluated in terms of frictional torque and energy consumption during tapping processes. This instrument can adapt onto any conventional milling machine or CNC machine and operate under various machining operations such as tapping, drilling, and other processes. To validate the design and performance of this new device, three commercially available lubricants were evaluated. From the three tested conditions, the results showed good repeatability, with consistent results …

Kidney-Related Operations Research: A Review, Mahdi Fathi, Marzieh Khakifirooz

BCoE Publications

Operations research and optimization in healthcare and disease modeling have received significant attention in the last three decades. This article surveys several perspectives of operations research techniques in kidney disease, such as graph theory, queueing theory, Markov chain, and phase-type distribution (PTD). The kidney-related problems include kidney exchange problem, the modeling of kidney disease progression, kidney transplantation, and the complex relationship between chronic kidney disease (gradual loss of kidney function over time) and acute kidney injury (sudden episode of kidney failure in a few hours or a few days). Each section is summarized by some discussion regarding the limitation of …

Extreme-Point Tabu Search Heuristics For Fixed-Charge Generalized Network Problems, Angelika Leskovskaya

Operations Research and Engineering Management Theses and Dissertations

While researchers have studied generalized network flow problems extensively, the powerful addition of fixed charges on arcs has received scant attention. This work describes network-simplex-based algorithms that efficiently exploit the quasi-tree basis structure of the problem relaxations, proposes heuristics that utilize a candidate list, a tabu search with short and intermediate term memories to do the local search, a diversification approach to solve fixed-charge transportation problems, as well as a dynamic linearization of objective function extension for the transshipment fixed-charge generalized problems. Computational testings for both heuristics demonstrate their effectiveness in terms of speed and quality of solutions to these …

Preface, Cihan H. Dagli, Gursel A. Suer

Engineering Management and Systems Engineering Faculty Research & Creative Works

No abstract provided.

Mars Knot Positioning And Global Optimization, Xinglong Ju

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Multivariate adaptive regression splines (MARS) is a statistical modeling approach with wide real-world applications. In the MARS model building process, knot positioning is a critical step that potentially affects the accuracy of the final MARS model. Identifying well-positioned knots entails assessing the quality of many knots in each model building iteration, which requires much computation efforts. By exploring the change in the residual sum of squares (RSS) within MARS, we find that local optima from previous iterations can be very close to those of the current iteration. In our approach, the prior change in RSS information is used to “warm …

Analyzing Collaboration In Food Assistance Networks Using Agent-Based Modeling, Joyita Mostafa

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

To address the issue of food insecurity, many small independent agencies, known as food pantries, collect and distribute donated food to food-insecure clients. However, the supply of donated food varies significantly from week to week, leading to frequent mismatches in supply and demand. One approach to addressing this problem is to facilitate greater food pantry collaboration, such that they are able to balance supply and demand among themselves. However, their interpersonal relationships and the additional costs associated with transshipments can be a barrier to collaboration. The objective of this research is to use modeling to gain a better understanding of …

Dynamic Prediction Of Treatment Outcomes For Recurrent Tuberculosis Patients, Nicole Hayes

Industrial Engineering Undergraduate Honors Theses

Tuberculosis (TB) is a disease that affects people around the world, especially people in underdeveloped countries. TB is one of the top ten causes of death globally so improvement in understanding diagnosis and treatment of TB affected patients could lead to major improvements in world health. This thesis research evaluated relapse patients specifically, deeming a relapse patient as one who has either been cured or completed their last treatment and then is diagnosed with TB again.

This research uses dynamic predictive modeling, based upon the random forest algorithm, to predict treatment outcomes for recurrent TB patients using demographic and follow-up …

Joint Manufacturing And Onsite Microgrid System Control Using Markov Decision Process And Neural Network Integrated Reinforcement Learning, Wenqing Hu, Zeyi Sun, Y. Zhang, Y. Li

Mathematics and Statistics Faculty Research & Creative Works

Onsite microgrid generation systems with renewable sources are considered a promising complementary energy supply system for manufacturing plant, especially when outage occurs during which the energy supplied from the grid is not available. Compared to the widely recognized benefits in terms of the resilience improvement when it is used as a backup energy system, the operation along with the electricity grid to support the manufacturing operations in non-emergent mode has been less investigated. In this paper, we propose a joint dynamic decision-making model for the optimal control for both manufacturing system and onsite generation system. Markov Decision Process (MDP) is …

System Of Systems (Sos) Architecture For Digital Manufacturing Cybersecurity, Lirim Ashiku, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

Technology advancements of real time connectivity and computing powers has evolved the way people manage activities triggering heavy reliance on smart devices. This has reshaped the ability to memorize crucial information, instead accumulate the information into devices allowing real-time fingertip access when needed. Inability to access such information when needed is routinely assumed with device malfunctioning bypassing the probability of compromise, but what if the information is now being accessed by adversaries depriving the data-owner access to crucial information? Cyber manufacturing systems are not immune from these issues. It is possible to approach this problem as generating SoS meta-architecture. In …

A Multi-Agent Demand Response Planning And Operational Optimization Framework, Alireza Fallahi

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

This research describes a real-time optimization model for multi-agent demand response (DR) from a Load Serving Entity (LSE) perspective. We formulate two infinite horizon stochastic optimization models; specifically, an LSE model and a dynamic pricing customer model. The objective of these models is to minimize long-term cost and discomfort penalty of the LSE and dynamic pricing customers. We solve a deterministic finite horizon linear program as an approximation of the suggested stochastic model and provide computational experiments. In stochastic programming (SP), a wait-and-see solution is at least as good as an optimal policy. On the other hand, a policy that …

Toolpath Planning Methodology For Multi-Gantry Fused Filament Fabrication 3d Printing, Hieu Trung Bui

Graduate Theses and Dissertations

Additive manufacturing (AM) has revolutionized the way industries manufacture and prototype products. Fused filament fabrication (FFF) is one of the most popular processes in AM as it is inexpensive, requires low maintenance, and has high material utilization. However, the biggest drawback that prevents FFF printing from being widely implemented in large-scale production is the cycle time. The most practical approach is to allow multiple collaborating printheads to work simultaneously on different parts of the same object. However, little research has been introduced to support the aforementioned approach. Hence a new toolpath planning methodology is proposed in this paper. The objectives …

Evaluation Of Data Collection Operations For Real-Time Influenza Surveillance During An Emergency, Yuwen Gu

Dissertations

It is unclear how data collection operations for surveillance alter the disease portrayal that influenza reported trends attempt to provide during an emergency. This study developed a model that simulates the collection and testing of influenza specimens after an outbreak is declared in Michigan. It performed simulation based optimization to understand which operational factors affect the biases between the growth rates of original and observed influenza incidence trends, and to quantify the predictive power of the influenza incidence trends at different points of data collection. The results show that emergency driven high risk perception increases the reporting, which leads to …

Automatic Methods To Enhance The Quality Of Colonoscopy Video, Nidhal Kareem Shukur Azawi

Graduate Theses and Dissertations

Colonoscopy is a form of endoscopy because it uses colonoscopy device to help the doctor to understand a colon patient. Enhancing the quality of Colonoscopy images is a challenge because of the wet and dynamic environment inside the colon causes many problems even the colonoscope devise has a good quality. Some of these problems are blurriness, specular highlights shiny areas.

In this work, different kinds of techniques have been investigated in order to improve the quality of colonoscopy images. Also, variety of preprocessing approaches (removing bad images, resizing images, median filtration with and without image resizing) have been conducted to …

A Framework Of Integrating Manufacturing Plants In Smart Grid Operation: Manufacturing Flexible Load Identification, Md. Monirul Islam, Zeyi Sun, Wenqing Hu, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

In the deregulated electricity markets run by Independent System Operator (ISO), a two-settlement (day-ahead and real-time) process is typically used to determine the electricity price to the end-use customers at different buses. In the day-ahead settlement, the demand is predicted at each bus based on the previous consumption behavior of the consumers and thus, Locational Marginal Price (LMP) can be determined and shared to the consumers. A significant gap is usually observed between the planned and real-time demands due to the uncertainties of the weather (temperature, wind-speed etc.), the intensity of business, and everyday activities. Therefore, a large price variation …

Uncovering Underlying Features For State Transition Modeling, Ashkan Farahani

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Modeling of a dynamic system is the representation of the interconnectivity of system state variables and their evolutionary trajectory over time. In this dissertation, the terminology “state transition modeling” refers to a situation when the system state transitions and its evolution is unknown and needs to be estimated. There are situations in many application settings where one does not simply observe the behavior of the system, but also has a desire to take action, intervene, and manipulate one or more system variables, and is interested in seeing the causal effect of the intervention. These interventions within a purely observational setting, …

Direct Assessment Of Entrepreneurial Minded Learning Through Integrated E-Learning Modules, Aadtiyasinh Rana

Master's Theses

Entrepreneurial Minded Learning (EML) has a significant emphasis in engineering education

today. Several approaches have been used to assess the impact of various EML approaches. Many indirect assessment techniques have been used and a few direct assessment techniques have been developed. The work presented in this thesis investigates the effectiveness of two specific measurement methods to quantify entrepreneurial minded learning in students.

The University of New Haven has adopted the approach of integrating e-learning modules on entrepreneurial topics and related contextual activities into courses as the primary approach of developing an entrepreneurial mindset (EM) in students. This study focuses on …

Action Recognition In Manufacturing Assembly Using Multimodal Sensor Fusion, Md. Al-Amin, Wenjin Tao, David Doell, Ravon Lingard, Zhaozheng Yin, Ming-Chuan Leu, Ruwen Qin

Computer Science Faculty Research & Creative Works

Production innovations are occurring faster than ever. 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 operation performance in near real-time will achieve better performance than peers. Action recognition can serve this purpose. Despite that human action recognition has been an active field of study in machine learning, limited work has been done for recognizing worker actions in performing manufacturing tasks that involve complex, intricate operations. Using data captured by one sensor or a single type of sensor to recognize …

Control Of Infectious Diseases In A Metapopulation, Ceyda Best

All Dissertations

With the motivation of the complex infectious disease control problem, we provide two different approaches to model the resource allocation problem to control an epidemic in a metapopulation. All of our models utilize a detailed stochastic simulation model that is validated with the data from the 2014 Ebola epidemic. This simulation model provides a tool for comparing the performance of different policies.

The first model defines a dynamic allocation problem, which is modeled by a Markov Decision Process, and aims to find feasible and effective quarantine policies to control an epidemic with limited resources. We assume that the populations share …

Data-Driven Surgical Duration Prediction Model For Surgery Scheduling: A Case-Study For A Practice-Feasible Model In A Public Hospital, Kar Way Tan, Francis Ngoc Hoang Long Nguyen, Boon Yew Ang, Jerald Gan, Sean Shao Wei Lam

Research Collection School Of Computing and Information Systems

Hospitals have been trying to improve the utilization of operating rooms as it affects patient satisfaction, surgery throughput, revenues and costs. Surgical prediction model which uses post-surgery data often requires high-dimensional data and contains key predictors such as surgical team factors which may not be available during the surgical listing process. Our study considers a two-step data-mining model which provides a practical, feasible and parsimonious surgical duration prediction. Our model first leverages on domain knowledge to provide estimate of the first surgeon rank (a key predicting attribute) which is unavailable during the listing process, then uses this predicted attribute and …

Simulated Annealing For The Multi-Vehicle Cyclic Inventory Routing Problem, Aldy Gunawan, Vincent F. Yu, Audrey Tedja Widjaja, Pieter Vansteenwegen

Research Collection School Of Computing and Information Systems

This paper studies the Multi-Vehicle Cyclic Inventory Routing Problem (MV-CIRP) as the extension of the Single-Vehicle CIRP (SV-CIRP). The objective is to minimize both distribution and inventory costs at the customers and to maximize the collected rewards simultaneously. The problem is treated as a single objective optimization problem. A subset of customers is selected for each vehicle including the quantity to be delivered to each customer. For each vehicle, a cyclic distribution plan is developed. We construct a mathematical programming model and propose a simulated annealing (SA) metaheuristic for solving both SV-CIRP and MV-CIRP. For SV-CIRP, experimental results on benchmark …

Correlation-Sensitive Next-Basket Recommendation, Duc Trong Le, Hady Wirawan Lauw, Yuan Fang

Research Collection School Of Computing and Information Systems

Items adopted by a user over time are indicative ofthe underlying preferences. We are concerned withlearning such preferences from observed sequencesof adoptions for recommendation. As multipleitems are commonly adopted concurrently, e.g., abasket of grocery items or a sitting of media consumption, we deal with a sequence of baskets asinput, and seek to recommend the next basket. Intuitively, a basket tends to contain groups of relateditems that support particular needs. Instead of recommending items independently for the next basket, we hypothesize that incorporating informationon pairwise correlations among items would help toarrive at more coherent basket recommendations.Towards this objective, we develop a …

Improving Law Enforcement Daily Deployment Through Machine Learning-Informed Optimization Under Uncertainty, Jonathan David Chase, Duc Thien Nguyen, Haiyang Sun, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Urban law enforcement agencies are under great pressure to respond to emergency incidents effectively while operating within restricted budgets. Minutes saved on emergency response times can save lives and catch criminals, and a responsive police force can deter crime and bring peace of mind to citizens. To efficiently minimize the response times of a law enforcement agency operating in a dense urban environment with limited manpower, we consider in this paper the problem of optimizing the spatial and temporal deployment of law enforcement agents to predefined patrol regions in a real-world scenario informed by machine learning. To this end, we …

Decision Making For Improving Maritime Traffic Safety Using Constraint Programming, Saumya Bhatnagar, Akshat Kumar, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Maritime navigational safety is of utmost importance to prevent vessel collisions in heavily trafficked ports, and avoid environmental costs. In case of a likely near miss among vessels, port traffic controllers provide assistance for safely navigating the waters, often at very short lead times. A better strategy is to avoid such situations from even happening. To achieve this, we a) formalize the decision model for traffic hotspot mitigation including realistic maritime navigational features and constraints through consultations with domain experts; and b) develop a constraint programming based scheduling approach to mitigate hotspots. We model the problem as a variant of …

Probabilistic Models For Order-Picking Operations With Multiple In-The-Aisle Pick Positions, Jingming Liu

Graduate Theses and Dissertations

The development of probability density functions (pdfs) for travel time of a narrow aisle lift truck (NALT) and an automated storage and retrieval (AS/R) machine is the focus of the dissertation. The multiple in-the-aisle pick positions (MIAPP) order picking system can be modeled as an M/G/1 queueing problem in which storage and retrieval requests are the customers and the vehicle (NALT or AS/R machine) is the server. Service time is the sum of travel time and the deterministic time to pick up and deposit a pallet (TPD).

Our first contribution is the development of travel time pdfs for retrieval operations …

Measuring Risks Of Interdependencies In Enterprise Systems: An Application To Ghana’S Salt Enterprise, Yaw Mensah

Engineering Management & Systems Engineering Theses & Dissertations

This dissertation describes the use of Functional Dependency Network Analysis (FDNA) for modeling risks resulting from dependencies among elements of enterprise systems with application to salt processing enterprise in Ghana. FDNA was developed to model dependencies among members of enterprise systems by highlighting two dimensions of dependency: strength and criticality. Nonetheless, the concepts and analytics for these two dimensions of dependencies needed further development and generalization in the context of project management and systems development in developing countries.

Managing risks within the interdependency in enterprise systems through integration will help improve global economic growth. Coherent theory for enterprise integration must …

Mid To Late Season Weed Detection In Soybean Production Fields Using Unmanned Aerial Vehicle And Machine Learning, Arun Narenthiran Veeranampalayam Sivakumar

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

Mid-late season weeds are those that escape the early season herbicide applications and those that emerge late in the season. They might not affect the crop yield, but if uncontrolled, will produce a large number of seeds causing problems in the subsequent years. In this study, high-resolution aerial imagery of mid-season weeds in soybean fields was captured using an unmanned aerial vehicle (UAV) and the performance of two different automated weed detection approaches – patch-based classification and object detection was studied for site-specific weed management. For the patch-based classification approach, several conventional machine learning models on Haralick texture features were …

Minimodal: Dimensional Domain Of Miniature Shipping Containers For Intermodal Freight Transportation, Lee Stapley

Ursidae: The Undergraduate Research Journal at the University of Northern Colorado

This study explores the feasibility of miniature shipping container usage within existing intermodal transportation (IT) supply chains. Smaller intermodal container shipments may help realign freight shipments with the most efficient transportation mode, rail. These containers embolden the dimensional domain (DD) of shipping. The shipping container dimensional domain (container size variation and modal fluidity) is widespread and results in shipments that are often larger or more infrequent than needed. The DD impacts transport mode, shipping frequency, shipment velocity, intermodal supply chain accessibility, and regional shipping networks. This study suggests that container size impacts the DD and, therefore, mode choice. As miniature …

Keeping Humans In The Loop: Pooling Knowledge Through Artificial Swarm Intelligence To Improve Business Decision Making, Lynn E. Metcalf, David A. Askay, Louis B. Rosenberg

Industrial Technology and Packaging

This article explores how a collaboration technology called Artificial Swarm Intelligence (ASI) addresses the limitations associated with group decision making, amplifies the intelligence of human groups, and facilitates better business decisions. It demonstrates of how ASI has been used by businesses to harness the diverse perspectives that individual participants bring to groups and to facilitate convergence upon decisions. It advances the understanding of how artificial intelligence (AI) can be used to enhance, rather than replace, teams as they collaborate to make business decisions.

Factors Influencing Revenue Collection For Preventative Maintenance Of Community Water Systems: A Fuzzy-Set Qualitative Comparative Analysis, Liesbet Olaerts, Jeffrey P. Walters, Karl G. Linden, Amy Javernick-Will, Adam Harvey

Faculty Publications - Biomedical, Mechanical, and Civil Engineering

This study analyzed combinations of conditions that influence regular payments for water service in resource-limited communities. To do so, the study investigated 16 communities participating in a new preventive maintenance program in the Kamuli District of Uganda under a public–private partnership framework. First, this study identified conditions posited as important for collective payment compliance from a literature review. Then, drawing from data included in a water source report and by conducting semi-structured interviews with households and water user committees (WUC), we identified communities that were compliant with, or suspended from, preventative maintenance service payments. Through qualitative analyses of these data …