Systems Engineering Commons^™

Using Strategic Options Development And Analysis (Soda) To Understand The Simulation Accessibility Problem, Andrew J. Collins, Ying Thaviphoke, Antuela A. Tako

Engineering Management & Systems Engineering Faculty Publications

Simulation modelling is applied to a wide range of problems, including defense and healthcare. However, there is a concern within the simulation community that there is a limited use and implementation of simulation studies in practice. This suggests that despite its benefits, simulation may not be reaching its potential in making a real-world impact. The main reason for this could be that simulation tools are not widely accessible in industry. In this paper, we investigate the issues that affect simulation modelling accessibility through a workshop with simulation practitioners. We use Strategic Options Development and Analysis (SODA), a problem-structuring approach that …

Study Of Stochastic Market Clearing Problems In Power Systems With High Renewable Integration, Saumya Sakitha Sashrika Ariyarathne

Operations Research and Engineering Management Theses and Dissertations

Integrating large-scale renewable energy resources into the power grid poses several operational and economic problems due to their inherently stochastic nature. The lack of predictability of renewable outputs deteriorates the power grid’s reliability. The power system operators have recognized this need to account for uncertainty in making operational decisions and forming electricity pricing. In this regard, this dissertation studies three aspects that aid large-scale renewable integration into power systems. 1. We develop a nonparametric change point-based statistical model to generate scenarios that accurately capture the renewable generation stochastic processes; 2. We design new pricing mechanisms derived from alternative stochastic programming …

The Intersection Of Robotic Process Automation And Lean Six Sigma Applied To Unstructured Data, Emily Mcintosh

Operations Research and Engineering Management Theses and Dissertations

While new Artificial Intelligence (AI) technologies gain traction in the workplace, there seems to be more buzz around these newer advances, including Robotic Process Automation (RPA), than more established process improvement techniques such as Lean Six Sigma. This praxis research uses Lean Six Sigma as a framework for effectively deploying these emerging technologies, a challenge for 86% of companies (Ernst & Young, 2021). This research is applied to one of the legal industry’s most resource intensive processes – eDiscovery in the environment of a Big 4 accounting firm that provides services to corporations and legal professionals alike.

Electronic discovery (also …

Supervised Representation Learning For Improving Prediction Performance In Medical Decision Support Applications, Phawis Thammasorn

Graduate Theses and Dissertations

Machine learning approaches for prediction play an integral role in modern-day decision supports system. An integral part of the process is extracting interest variables or features to describe the input data. Then, the variables are utilized for training machine-learning algorithms to map from the variables to the target output. After the training, the model is validated with either validation or testing data before making predictions with a new dataset. Despite the straightforward workflow, the process relies heavily on good feature representation of data. Engineering suitable representation eases the subsequent actions and copes with many practical issues that potentially prevent the …

The Impact Of Reliability In Conceptual Design - An Integrated Trade-Off Analysis, Tevari James Barker

Graduate Theses and Dissertations

Research presented in this paper focuses on developing models to estimate the systemreliability of Unmanned Ground Vehicles using knowledge and data from similar systems. Traditional reliability approaches often require detailed knowledge of a system and are used in later design stages as well as development, operational test and evaluation, and operations. The critical role of reliability and its impact on acquisition program performance, cost, and schedule motivate the need for improved system reliability models in the early design stages. Reliability is often a stand-alone requirement and not fully included in performance and life cycle cost models. This research seeks to …

Comparing Actively Managed Mutual Fund Categories To Index Funds Using Linear Regression Forecasting And Portfolio Optimization, Luke Weiner

Industrial Engineering Undergraduate Honors Theses

The global investment industry offers a wide variety of investment products especially for individual investors. One such product, index funds, which are younger than actively managed mutual funds, have typically outperformed managed funds. Despite this phenomenon, investors have displayed a tendency to continue investing in actively managed funds. Although only a small percentage of actively managed funds outperform index funds, the costs of actively managed funds are significantly higher. Also, managed fund performances are most often determined by their fund category such as growth or real estate. I wanted to answer the following question for individual investors: can we …

Forecasting Hypotension By Learning From Multivariate Mixed Responses.., Jodie Ritter

Electronic Theses and Dissertations

Blood Pressure is the main determinant of blood flow to organs. Hypotension is defined as a systolic blood pressure less than 90 mmHg or a diastolic blood pressure less than 50 mmHg. The severity and duration of hypotension is associated with low blood flow to organs often result in organ damage and a high mortality rate. Predicting hypotension prior to surgery and during the surgery can reduce the incidence and duration resulting in better patient outcomes. This thesis uses preoperative bloodwork and vital signs as well as perioperative vital signs in 5-minute increments as inputs to forecast hypotension. Hypotension can …

Complex System Governance Leadership, David C. Walters

Engineering Management & Systems Engineering Theses & Dissertations

The purpose of this research was to develop a systems theory-based framework for leadership in governance of complex systems. Recognizing complexity and uncertainty as norms for the environments in which organizations exist encouraged researchers to suggest complexity theory, complex systems, and complex adaptive systems as appropriate for addressing these conditions. Complex System Governance (CSG), based in systems theory, management cybernetics, and governance, endeavors to provide for the design, execution and evolution of functions that provide control, communication, coordination, and integration at the metasystem level to support operations and continued system existence (viability). From a management cybernetics perspective, CSG leadership has …

An Elliptical Cover Problem In Drone Delivery Network Design And Its Solution Algorithms, Yanchao Liu

Industrial and Systems Engineering Faculty Research Publications

Given n demand points in a geographic area, the elliptical cover problem is to determine the location of p depots (anywhere in the area) so as to minimize the maximum distance of an economical delivery trip in which a delivery vehicle starts from the nearest depot to a demand point, visits the demand point and then returns to the second nearest depot to that demand point. We show that this problem is NP-hard, and adapt Cooper’s alternating locate-allocate heuristic to find locally optimal solutions for both the point-coverage and area-coverage scenarios. Experiments show that most locally optimal solutions perform similarly …

The Traveling Salesman Problem: An Analysis And Comparison Of Metaheuristics And Algorithms, Mason Helmick

Senior Honors Theses

One of the most investigated topics in operations research is the Traveling Salesman Problem (TSP) and the algorithms that can be used to solve it. Despite its relatively simple formulation, its computational difficulty keeps it and potential solution methods at the forefront of current research. This paper defines and analyzes numerous proposed solutions to the TSP in order to facilitate understanding of the problem. Additionally, the efficiencies of different heuristics are studied and compared to the aforementioned algorithms’ accuracy, as a quick algorithm is often formulated at the expense of an exact solution.

Decision-Analytic Models Using Reinforcement Learning To Inform Dynamic Sequential Decisions In Public Policy, Seyedeh Nazanin Khatami

Doctoral Dissertations

We developed decision-analytic models specifically suited for long-term sequential decision-making in the context of large-scale dynamic stochastic systems, focusing on public policy investment decisions. We found that while machine learning and artificial intelligence algorithms provide the most suitable frameworks for such analyses, multiple challenges arise in its successful adaptation. We address three specific challenges in two public sectors, public health and climate policy, through the following three essays. In Essay I, we developed a reinforcement learning (RL) model to identify optimal sequence of testing and retention-in-care interventions to inform the national strategic plan “Ending the HIV Epidemic in the US”. …

The Toyota Production System (Tps) In A Non-Traditional Manufacturing Environment: The Role Of Standardization In The Fast-Food Industry, Kevin Mccracken

Theses and Dissertations--Manufacturing Systems Engineering

The Toyota Production System (TPS), also known as Lean Manufacturing (LM), was founded in the automotive industry and has contributed to Toyota’s decades of success. This has brought much attention to TPS and how this system may be implemented in other industries. Focusing on the TPS foundational element of standardization, this study examines the impact of target cycle time (TCT) on process fluctuation in a fast-food environment. In order to observe the effects of TCT, team members within 3 production lines were timed. Times were measured before and after the addition of a TCT to the Standardized Work (STW) in …

Simulation-Based Optimization: Implications Of Complex Adaptive Systems And Deep Uncertainty, Andreas Tolk

VMASC Publications

Within the modeling and simulation community, simulation-based optimization has often been successfully used to improve productivity and business processes. However, the increased importance of using simulation to better understand complex adaptive systems and address operations research questions characterized by deep uncertainty, such as the need for policy support within socio-technical systems, leads to the necessity to revisit the way simulation can be applied in this new area. Similar observations can be made for complex adaptive systems that constantly change their behavior, which is reflected in a continually changing solution space. Deep uncertainty describes problems with inadequate or incomplete information about …

Quantitative Methods For Total Lifecycle Risk Likelihood And Impact Assessment In Sustainable Product Design Decision Making, Christian Enyoghasi

Theses and Dissertations--Mechanical Engineering

Sustainable products promise significant economic, environmental, and societal benefits. Numerous methods are available for use during the new product development process to identify alternate product designs that optimize sustainability performance. Once any such design is selected and the product is launched, many uncertainties are likely to affect its performance over the total lifecycle. Such uncertainties give rise to risks that can influence the overall product sustainability performance. However, comprehensive quantitative methods to evaluate the likelihood or the impact of different risks to enable sustainable product design decision making are lacking.

This research aims to address this gap by developing a …