Engineering Commons^™

Statistical Modeling, Learning And Computing For Stochastic Dynamics Of Complex Systems, Mohammadmahdi Hajiha

Graduate Theses and Dissertations

With the recent advances in sensor technology, it is much easier to collect and store streams of system operational and environmental (SOE) data. These data can be used as input to model the underlying behavior of complex engineered systems and phenomenons if appropriate algorithms with well-defined assumptions are developed. This dissertation is comprised of the research work to show the applicability of SOE data when fed into proposed tailored algorithms. The first purposes of these algorithms are to estimate and analyze the reliability of a system as elaborated in Chapter 2. This chapter provides the derivation of closed-form expressions that …

Scheduling Allocation And Inventory Replenishment Problems Under Uncertainty: Applications In Managing Electric Vehicle And Drone Battery Swap Stations, Amin Asadi

Graduate Theses and Dissertations

In this dissertation, motivated by electric vehicle (EV) and drone application growth, we propose novel optimization problems and solution techniques for managing the operations at EV and drone battery swap stations. In Chapter 2, we introduce a novel class of stochastic scheduling allocation and inventory replenishment problems (SAIRP), which determines the recharging, discharging, and replacement decisions at a swap station over time to maximize the expected total profit. We use Markov Decision Process (MDP) to model SAIRPs facing uncertain demands, varying costs, and battery degradation. Considering battery degradation is crucial as it relaxes the assumption that charging/discharging batteries do not …

A Machine Learning Approach To Understanding Emerging Markets, Namita Balani

Graduate Theses and Dissertations

Logistic providers have learned to efficiently serve their existing customer bases with optimized routes and transportation resource allocation. The problem arises when there is potential for logistics growth in an emerging market with no previous data. The purpose of this work is to use industry data for previously known and well-documented markets to apply data analytic techniques such as machine learning to investigate the uncertainty in a new market. The thesis looks into machine learning techniques to predict miles per stop given historical data. It mainly focuses on Random Forest Regression Analysis, but concludes that additional techniques, such as Polynomial …

Optimization Of Vaccine Supply Chains In Low- And Middle-Income Countries Utilizing Drones, Maximilian Kolter

Graduate Theses and Dissertations

Despite tremendous efforts from governments and humanitarian organizations, millions of children in low- and low-middle-income countries (LICs and LMICs) are still excluded from the benefits of immunization. The vaccine distribution in LICs and LMICs is challenging for several reasons, such as limited cold chain capacities, vaccine wastage, uncertain demand, and lack of access to immunization services. A promising avenue to address these issues is the utilization of drones for vaccine delivery. Drones can fly at high speed on direct paths and could enable on-demand deliveries to mitigate limited storage capacities. Further, their independence of road networks could allow them reaching …

Enabling The “Easy Button” For Broad, Parallel Optimization Of Functions Evaluated By Simulation, Andrew Gibson

Graduate Theses and Dissertations

Java Optimization by Simulation (JOBS) is presented: an open-source, object-oriented Java library designed to enable the study, research, and use of optimization for models evaluated by simulation. JOBS includes several novel design features that make it easy for a simulation modeler, without extensive expertise in optimization or parallel computation, to define an optimization model with deterministic and/or stochastic constraints, choose one or more metaheuristics to solve it and run, using massively parallel function evaluation to reduce wall-clock times.

JOBS is supported by a new language independent, application programming interface (API) for remote simulation model evaluation and a serverless computing environment …

Resilience-Driven Post-Disruption Restoration Of Interdependent Critical Infrastructure Systems Under Uncertainty: Modeling, Risk-Averse Optimization, And Solution Approaches, Basem A. Alkhaleel

Graduate Theses and Dissertations

Critical infrastructure networks (CINs) are the backbone of modern societies, which depend on their continuous and proper functioning. Such infrastructure networks are subjected to different types of inevitable disruptive events which could affect their performance unpredictably and have direct socioeconomic consequences. Therefore, planning for disruptions to CINs has recently shifted from emphasizing pre-disruption phases of prevention and protection to post-disruption studies investigating the ability of critical infrastructures (CIs) to withstand disruptions and recover timely from them. However, post-disruption restoration planning often faces uncertainties associated with the required repair tasks and the accessibility of the underlying transportation network. Such challenges are …

Quantitative Set-Based Design For Complex System Development, Nicholas J. Shallcross

Graduate Theses and Dissertations

This dissertation comprises a body of research facilitating decision-making and complex system development with quantitative set-based design (SBD). SBD is concurrent product development methodology, which develops and analyzes many design alternatives for longer time periods enabling design maturation and uncertainty reduction. SBD improves design space exploration, facilitating the identification of resilient and affordable systems. The literature contains numerous qualitative descriptions and quantitative methodologies describing limited aspects of the SBD process. However, there exist no methodologies enabling the quantitative management of SBD programs throughout the entire product development cycle. This research addresses this knowledge gap by developing the process framework and …

Deployment Policies To Reliably Maintain And Maximize Expected Coverage In A Wireless Sensor Network, Nicholas T. Boardman

Graduate Theses and Dissertations

The long-term operation of a wireless sensor network (WSN) requires the deployment of new sensors over time to restore any loss in network coverage and communication ability resulting from sensor failures. Over the course of several deployment actions it is important to consider the cost of maintaining the WSN in addition to any desired performance measures such as coverage, connectivity, or reliability. The resulting problem formulation is approached first through a time-based deployment model in which the network is restored to a fixed size at periodic time intervals. The network destruction spectrum (D-spectrum) has been introduced to estimate reliability and …

Knowledge Discovery From Complex Event Time Data With Covariates, Samira Karimi

Graduate Theses and Dissertations

In particular engineering applications, such as reliability engineering, complex types of data are encountered which require novel methods of statistical analysis. Handling covariates properly while managing the missing values is a challenging task. These type of issues happen frequently in reliability data analysis. Specifically, accelerated life testing (ALT) data are usually conducted by exposing test units of a product to severer-than-normal conditions to expedite the failure process. The resulting lifetime and/or censoring data are often modeled by a probability distribution along with a life-stress relationship. However, if the probability distribution and life-stress relationship selected cannot adequately describe the underlying failure …

Efficiently Estimating Survival Signature And Two-Terminal Reliability Of Heterogeneous Networks Through Multi-Objective Optimization, Daniel Bruno Lopes Da Silva

Graduate Theses and Dissertations

The two-terminal reliability problem is a classical reliability problem with applications in wired and wireless communication networks, electronic circuit design, computer networks, and electrical power distribution, among other systems. However, the two-terminal reliability problem is among the hardest combinatorial problems and is intractable for large, complex networks. Several exact methods to solve the two-terminal reliability problem have been proposed since the 1960s, but they have exponential time complexity in general. Hence, practical studies involving large network-type systems resort to approximation methods to estimate the system's reliability. One attractive approach for quantifying the reliability of complex systems is to use signatures, …

An Examination Of Grid Stability As It Relates To The Increased Integration Of Inverter-Based Resources, Daniel Voss

Electrical Engineering Undergraduate Honors Theses

There is currently a growing interest in increasing the amount of renewable energy resources connected to the bulk electric system (BES) that stems from various environmental, political, and social concerns. However, the differences between conventional generation resources and inverter-based resources (IBR)—namely wind and solar—pose new issues that make this increased integration a larger problem. In other studies, the increased penetration of renewable energy resources has resulted in weak-grid systems that are more susceptible to collapse. This comes as a result from the inability for IBRs to effectively provide enough reactive power, an effect especially apparent during fault conditions, which the …

Regression Analysis Of Pacing When Running A Marathon, Hawkin Starke

Industrial Engineering Undergraduate Honors Theses

Regression analysis can be an effective way of examining performance in the marathon event. By splitting up the race into segments or in runner terminology “splits” the significance of each segment as it relates to the total finish time can be explored. Because the idea of splits is already ingrained into the minds of runners, it makes intuitive sense to use these as the metrics to define a race. Additionally, marathons generally make participant age and gender date publicly available which can then be used to find trends within specific demographics. This tailors trends to smaller groups of people, making …

Improving Logistics Efficiency Through Collaborative Truck Routing, Patrick Dougherty

Industrial Engineering Undergraduate Honors Theses

The logistics industry is among the world’s largest and most essential. Specifically, trucking is a massive component of the modern logistics system. In 2012, truck transportation carried 68% of all freight tonnage in the U.S. However, trucking currently faces significant problems with efficiency and sustainability. Of all miles driven by trucks yearly in the U.S., 25% are driven with empty loads and 36% are driven with underutilized loads. In addition to this economic inefficiency, the industry faces social and environmental challenges. Driver turnover rates are near 100%, and trucking accounts for a significant level of greenhouse gas emissions. One potential …

Noise Control In Sorting Conveyors, Eyra Herrera

Mechanical Engineering Undergraduate Honors Theses

E-commerce has increased the necessity of effective material handling equipment in warehouses and distribution centers. Sorter conveyors systems facilitate material handling by providing a reliable and automated system to classify and distribute products in a gentle and rapid manner. With the steady increase of speed in sorter conveyors to satisfy today’s industry demand, some systems have started to produce high noise levels that could potentially affect workers’ health. Since decreasing the speed of these conveyors is not a viable option to decrease noise in sorter equipment, industries have opted to find other ways to apply noise control to their equipment. …

Locating Drone Battery Supply Stations To Facilitate The Delivery Of Medical Supplies In Low And Middle-Income Countries, Madeline Suellentrop

Industrial Engineering Undergraduate Honors Theses

In the sub-Saharan region of Africa, the inability to perform emergency blood transfusions due to an inadequate blood supply has led to high fatality rates, especially among women and children. The prevalence of disease in this region limits the supply of local blood donations and, if blood is imported, then the region’s poor infrastructure inhibits fast distribution. There is a need for a technological update in the current process that overcomes the limitations of regional transportation, and drones present one promising solution for delivering small, lightweight items such as blood units. The current focus of this new delivery method is …

Decision Making Within An Nfl Context Using Multiple Objective Decision Analysis, Lawson Porter

Industrial Engineering Undergraduate Honors Theses

The National Football League (NFL) is the most popular sports league in the world, with millions of viewers every game and billions of dollars generated every season. Statistics are an important part of an NFL team’s business operating model and contribute greatly towards their decision making. Every season, general managers try to sign players that give the team the highest probability of winning games throughout the year. There are many factors that go into this decision, including the amount of money the team has to spend and the value that available players can bring to a team. Teams must abide …

Quantifying The Benefits Of A Collaborative Supply Chain Network Using A Discrete-Time Vehicle Routing Model, Matthew Walters

Industrial Engineering Undergraduate Honors Theses

The transportation industry contributed around one trillion dollars to the economy in 2016 accounting for 8.9% percent of the GDP. In 2017, it was responsible for 1.5 billion tons of CO₂ emissions. With the American Trucking agency predicting a 35% growth in the trucking industry between 2016 and 2027, there are rising concerns about the impact the trucking industry will have on the economy and the environment. The trucking industry is also very inefficient with many trucks driving with empty loads or with less than full capacity loads. There is potential to save billions of dollars and cut back …