Physical Sciences and Mathematics Commons^™

Sequential Optimization For Stressor-Informed Test Planning Through Integration Of Experimental And Simulated Data, Jacob Brecheisen

Data Science Undergraduate Honors Theses

This technical report details an innovative approach in reliability engineering aimed at maximizing system durability through a synergistic use of physical experimentation and computer-based modeling. Our methodology explores the efficient design and analysis of computer experiments and physical tests to facilitate accelerated reliability growth, while leveraging a sequential integration of data from these two distinct sources: costly physical experiments, characterized by random errors, and inexpensive computer simulations, marked by inherent systematic errors. The key innovation lies in the adoption of a closed-loop design and analysis method. This method begins by identifying a viable subset of important environmental stressors—such as temperature, …

A Machine Learning Approach For Predicting Clinical Trial Patient Enrollment In Drug Development Portfolio Demand Planning, Ahmed Shoieb

Masters Theses

One of the biggest challenges the clinical research industry currently faces is the accurate forecasting of patient enrollment (namely if and when a clinical trial will achieve full enrollment), as the stochastic behavior of enrollment can significantly contribute to delays in the development of new drugs, increases in duration and costs of clinical trials, and the over- or under- estimation of clinical supply. This study proposes a Machine Learning model using a Fully Convolutional Network (FCN) that is trained on a dataset of 100,000 patient enrollment data points including patient age, patient gender, patient disease, investigational product, study phase, blinded …

Development Of Software Tools For Efficient And Sustainable Process Development And Improvement, Jake P. Stengel

Theses and Dissertations

Infrastructure is a key component in the well-being of our society that leads to its growth, development, and productive operations. A well-built infrastructure allows the community to be more competitive and promotes economic advancement. In 2021, the ASCE (American Society of Civil Engineers) ranked the American infrastructure as substandard, with an overall grade of C-. The overall ranking suffers when key infrastructure categories are not maintained according to the needs of the population. Therefore, there is a need to consider alternative methods to improve our infrastructure and make it more sustainable to enhance the overall grade. One of the challenges …

Energy Planning Model Design For Forecasting The Final Energy Consumption Using Artificial Neural Networks, Haidy Eissa

Theses and Dissertations

“Energy Trilemma” has recently received an increasing concern among policy makers. The trilemma conceptual framework is based on three main dimensions: environmental sustainability, energy equity, and energy security. Energy security reflects a nation’s capability to meet current and future energy demand. Rational energy planning is thus a fundamental aspect to articulate energy policies. The energy system is huge and complex, accordingly in order to guarantee the availability of energy supply, it is necessary to implement strategies on the consumption side. Energy modeling is a tool that helps policy makers and researchers understand the fluctuations in the energy system. Over the …

Optimal Communication Structures For Concurrent Computing, Andrii Berdnikov

Doctoral Dissertations

This research focuses on communicative solvers that run concurrently and exchange information to improve performance. This “team of solvers” enables individual algorithms to communicate information regarding their progress and intermediate solutions, and allows them to synchronize memory structures with more “successful” counterparts. The result is that fewer nodes spend computational resources on “struggling” processes. The research is focused on optimization of communication structures that maximize algorithmic efficiency using the theoretical framework of Markov chains. Existing research addressing communication between the cooperative solvers on parallel systems lacks generality: Most studies consider a limited number of communication topologies and strategies, while the …

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 …

Computational Model For Neural Architecture Search, Ram Deepak Gottapu

Doctoral Dissertations

"A long-standing goal in Deep Learning (DL) research is to design efficient architectures for a given dataset that are both accurate and computationally inexpensive. At present, designing deep learning architectures for a real-world application requires both human expertise and considerable effort as they are either handcrafted by careful experimentation or modified from a handful of existing models. This method is inefficient as the process of architecture design is highly time-consuming and computationally expensive.

The research presents an approach to automate the process of deep learning architecture design through a modeling procedure. In particular, it first introduces a framework that treats …

Developing Optimization Techniques For Logistical Tendering Using Reverse Combinatorial Auctions, Jennifer Kiser

Electronic Theses and Dissertations

In business-to-business logistical sourcing events, companies regularly use a bidding process known as tendering in the procurement of transportation services from third-party providers. Usually in the form of an auction involving a single buyer and one or more sellers, the buyer must make decisions regarding with which suppliers to partner and how to distribute the transportation lanes and volume among its suppliers; this is equivalent to solving the optimization problem commonly referred to as the Winner Determination Problem. In order to take into account the complexities inherent to the procurement problem, such as considering a supplier’s network, economies of scope, …

Renewable Energy Systems Optimization Using Monte Carlo Simulation And Evolutionary Algorithms, Nicolas Lopez

Open Access Theses & Dissertations

This Dissertation explores the Renewable Energy Integration Problem, and proposes a Genetic Algorithm embedded with a Monte Carlo simulation to solve large instances of the problem that are impractical to solve via full enumeration. The Renewable Energy Integration Problem is defined as finding the optimum set of components to supply the electric demand to a hybrid

microgrid. The components considered are solar panels, wind turbines, diesel generators, electric batteries, connections to the power grid and converters, which can be inverters and/or rectifiers. The methodology developed is explained as well as the combinatorial formulation. In addition, 2 case studies of a …

Warranty Period And Product Price Optimization For Remanufactured Products, Yuxi Liu

Theses and Dissertations

This study considers a remanufactured electrical product under a tiered warranty policy. Warranty is key in ensuring a good manufacturer—consumer relationship. Manufacturers hope to minimize warranty costs while consumers believe that good warranty promises better product quality and reliability. This Thesis presents an optimal warranty period from the perspective of a manufacturer to maximize the total expected profits, while ensuring sustained consumer relation. We use real data from a local company with a global supply chain to provide a numerical example.

Developing An Optimal Model For Infant Home Visitation, Isaac Atuahene

Doctoral Dissertations

The United States, Great Britain, Denmark, Canada and many other countries have accepted home visitation (HV) as a promising strategy for interventions for infants after births and for their mothers. Prior HV studies have focused on theoretical foundations, evaluations of programs, cost/benefit analysis and cost estimation by using hospital/payer/insurance data to prove its effectiveness and high cost. As governments and private organizations continue to fund HVs, it is an opportune time to develop and formulate operations research (OR) models of HV coverage, quality and cost so they might be used in program implementation as done for adult home healthcare (HHC) …

Mathematical Modeling For Platform-Based Product Configuration Considering Total Life-Cycle Sustainability, Tian Lan

Theses and Dissertations--Mechanical Engineering

Many companies are using platform-based product designs to fulfill the requirements of customers while maintaining low cost. However, research that integrates sustainability into platform-based product design is still limited. Considering sustainability during platform-based design process is a challenge because the total life-cycle from pre-manufacturing, manufacturing and use to post-use stages as well as economic, environmental and societal performance in these stages must be considered. In this research, an approach for quantifying sustainability is introduced and a mathematical model is developed for identifying a more sustainable platform. Data from life-cycle assessment is used to quantify environmental factors; criteria from the Product …

A Framework And System For A Multi-Model Decision Aid For Sustainable Farming Practices, Kasi Bharath Vegesana

Computational Modeling & Simulation Engineering Theses & Dissertations

Decision support systems (DSS) for farmers address the need for modeling multiple processes and scenarios that affect farmer decision making. Existing DSS have various drawbacks that stop them from being deployed as decision support tools. This research proposes a multi-model simulation framework that can be used to analyze farm management practices at the crop level, individual farm level and at the community level to show the impact and alternatives for smallholder farming practices. A generic crop growth model is proposed, based on existing equations. We run sensitivity analysis on the model to identify important variables. The outputs from the crop …

Truckload Shipment Planning And Procurement, Neo Nguyen

Graduate Theses and Dissertations

This dissertation presents three issues encountered by a shipper in the context of truckload transportation. In all of the studies, we utilize optimization techniques to model and solve the problems. Each study is inspired from the real world and much of the data used in the experiments is real data or representative of real data.

The first topic is about the freight consolidation in truckload transportation. We integrate it with a purchase incentive program to increase truckload utilization and maximize profit. The second topic is about supporting decision making collaboration among departments of a manufacturer. It is a bi-objective optimization …

Poisson Distributed Individuals Control Charts With Optimal Limits, Negin Enayaty Ahangar

Graduate Theses and Dissertations

The conventional method used in attribute control charts is the Shewhart three sigma limits. The implicit assumption of the Normal distribution in this approach is not appropriate for skewed distributions such as Poisson, Geometric and Negative Binomial. Normal approximations perform poorly in the tail area of the these distributions. In this research, a type of attribute control chart is introduced to monitor the processes that provide count data. The economic objective of this chart is to minimize the cost of its errors which is determined by the designer. This objective is a linear function of type I and II errors. …

Scheduling And Resource Allocation In Wireless Sensor Networks, Yosef Alayev

Dissertations, Theses, and Capstone Projects

In computer science and telecommunications, wireless sensor networks are an active research area. Each sensor in a wireless sensor network has some pre-defined or on demand tasks such as collecting or disseminating data. Network resources, such as broadcast channels, number of sensors, power, battery life, etc., are limited. Hence, a schedule is required to optimally allocate network resources so as to maximize some profit or minimize some cost. This thesis focuses on scheduling problems in the wireless sensor networks environment. In particular, we study three scheduling problems in the wireless sensor networks: broadcast scheduling, sensor scheduling for area monitoring, and …

Optimization Of Strategic Planning Processes For Configurable Products: Considerations For Global Supply, Demand, And Sustainability Issues, Edward Lawrence Umpfenbach

Wayne State University Dissertations

The assortment planning problem is to decide on the set of products that a retailer or manufacturer will offer to its customers to maximize profitability. While assortment planning research has been expanding in recent years, the current models are inadequate for the needs of a configurable product manufacturer. In particular, we address assortment planning for an automobile manufacturer. We develop models to integrate assortment planning and supply chain management, designed for use by a large automaker in its strategic planning phase. Our model utilizes a multinomial logit model transformed into a mixed integer linear program through the Charnes-Cooper transformation. It …

Computer-Based Methods For Constructing Two-Level Fractional-Factorial Experimental Designs With A Requirement Set, Steven L. Forsythe

Theses and Dissertations

This dissertation developed four methodologies for computer-aided experimental design of two-level fractional factorial designs with requirement sets (DOE/RS). The requirement sets identify all the experimental factors and the appropriate interaction terms to be evaluated in the experiment. Taguchi graphs and similar manual methods provide techniques for solving the DOE/RS problem. Unfortunately, these methods are limited because they become difficult to use as the number of factors or interaction terms exceeds ten. This research showed that the DOE/RS problem belongs to a class of difficult-to-solve problems known as NP-Complete. It is the combinatorial nature of NP-Complete problems that causes them to …