Physical Sciences and Mathematics Commons^™

High Multiplicity Strip Packing Problem With Three Rectangle Types, Andy Yu

Electronic Thesis and Dissertation Repository

The two-dimensional strip packing problem (2D-SPP) involves packing a set R = {r₁, ..., r_n} of n rectangular items into a strip of width 1 and unbounded height, where each rectangular item r_i has width 0 < w_i ≤ 1 and height 0 < h_i ≤ 1. The objective is to find a packing for all these items, without overlaps or rotations, that minimizes the total height of the strip used. 2D-SPP is strongly NP-hard and has practical applications including stock cutting, scheduling, and reducing peak power demand in smart-grids.

This thesis considers …

Electromagnetic Analysis Of Bidirectional Reflectance From Roughened Surfaces And Applications To Surface Shape Recovery, Julian Antolin Camarena

Physics & Astronomy ETDs

Scattering from randomly rough surfaces is a well-established sub area of electrodynamics. There remains much to be done since each surface and optical processes that may occur in within the scattering medium, and countless other scenarios, is different. There are also illumination models that describe lighting in a scene on the macroscopic scale where geometrical optics can be considered adequate. Of particular interest for us is the intersection of the physical scattering theories and the illumination models. We present two contributions: 1) A minimum of two independent images are needed since any opaque surface can be uniquely specified in terms …

Interactive Fitness Domains In Competitive Coevolutionary Algorithm, Atm Golam Bari

USF Tampa Graduate Theses and Dissertations

Evolutionary Algorithms (EA) have been successfully applied to a wide range of optimization and search problems where no mathematical model of the quality of a candidate solution is available. Interactive Evolutionary Algorithms (IEA) and Competitive Coevolutionary Algorithms (CCoEA) go one step further by being able to tackle problems where the only means to evaluate the quality of a candidate solution is via interactions. In a typical IEA, interactions take place between the solution being evolved and human evaluators. In a CCoEA, interactions take place between solutions themselves, without need for human interaction. This dissertation identifies computer-aided learning as an application …

Optimal Sampling Paths For Autonomous Vehicles In Uncertain Ocean Flows, Andrew J. De Stefan

Dissertations

Despite an extensive history of oceanic observation, researchers have only begun to build a complete picture of oceanic currents. Sparsity of instrumentation has created the need to maximize the information extracted from every source of data in building this picture. Within the last few decades, autonomous vehicles, or AVs, have been employed as tools to aid in this research initiative. Unmanned and self-propelled, AVs are capable of spending weeks, if not months, exploring and monitoring the oceans. However, the quality of data acquired by these vehicles is highly dependent on the paths along which they collect their observational data. The …

An Information Theory Model For Optimizing Quantitative Magnetic Resonance Imaging Acquisitions, Drew Mitchell

Dissertations & Theses (Open Access)

Quantitative magnetic resonance imaging (qMRI) is a powerful group of imaging techniques with a growing number of clinical applications, including synthetic image generation in post-processing, automatic segmentation, and diagnosis of disease from quantitative parameter values. Currently, acquisition parameter selection is performed empirically for quantitative MRI. Tuning parameters for different scan times, tissues, and resolutions requires some measure of trial and error. There is an opportunity to quantitatively optimize these acquisition parameters in order to maximize image quality and the reliability of the previously mentioned methods which follow image acquisition.

The objective of this work is to introduce and evaluate a …

Structured Sparsity Promoting Functions: Theory And Applications, Erin Tripp

Dissertations - ALL

Motivated by the minimax concave penalty based variable selection in high-dimensional linear regression, we introduce a simple scheme to construct structured semiconvex sparsity promoting functions from convex sparsity promoting functions and their Moreau envelopes. Properties of these functions are developed by leveraging their structure. In particular, we show that the behavior of the constructed function can be easily controlled by assumptions on the original convex function. We provide sparsity guarantees for the general family of functions via the proximity operator. Results related to the Fenchel Conjugate and Łojasiewicz exponent of these functions are also provided. We further study the behavior …

A Decision-Making Framework For Hybrid Resource Recovery Oriented Wastewater Systems, Nader Rezaei

USF Tampa Graduate Theses and Dissertations

Water shortage, water contamination, and the emerging challenges in sustainable water resources management (e.g., the likely impacts of climate change and population growth) necessitate adopting a reverse logistics approach, which is the process of moving wastewater from its typical final destination back to the water supply chain for reuse purposes. This practice not only reduces the negative impacts of wastewater on the environment, but also provides an alternative to withdrawal from natural water resources, forming a closed-loop water supply chain. However, the design of such a supply chain requires an appropriate sustainability assessment, which simultaneously accounts for economic, environmental, and …

Paper Structure Formation Simulation, Tyler R. Seekins

Electronic Theses and Dissertations

On the surface, paper appears simple, but closer inspection yields a rich collection of chaotic dynamics and random variables. Predictive simulation of paper product properties is desirable for screening candidate experiments and optimizing recipes but existing models are inadequate for practical use. We present a novel structure simulation and generation system designed to narrow the gap between mathematical model and practical prediction. Realistic inputs to the system are preserved as randomly distributed variables. Rapid fiber placement (~1 second/fiber) is achieved with probabilistic approximation of chaotic fluid dynamics and minimization of potential energy to determine flexible fiber conformations. Resulting digital packed …

Framework For Algorithmically Optimizing Longitudinal Health Outcomes: Examples In Cancer Radiotherapy And Occupational Radiation Protection, Lydia Joyce Wilson

LSU Doctoral Dissertations

Background: Advancements in the treatment of non-infectious disease have enabled survival rates to steadily increase in recent decades (e.g., diabetes, heart disease, and cancer). Epidemiological studies have revealed that the treatments for these diseases can have life-threatening and/or life–altering effects. Thus, realizing the full beneficial potential of advanced treatments necessitates new tools to algorithmically consider all major components of the health outcome, including benefit and detriment. The goal of this dissertation was to develop a framework for improving projected health outcomes following planned radiation exposures in consideration of all beneficial and detrimental, early and late, and fatal and non-fatal …

Gem-Pso: Particle Swarm Optimization Guided By Enhanced Memory, Kevin Fakai Chen

Honors Projects

Particle Swarm Optimization (PSO) is a widely-used nature-inspired optimization technique in which a swarm of virtual particles work together with limited communication to find a global minimum or optimum. PSO has has been successfully applied to a wide variety of practical problems, such as optimization in engineering fields, hybridization with other nature-inspired algorithms, or even general optimization problems. However, PSO suffers from a phenomenon known as premature convergence, in which the algorithm's particles all converge on a local optimum instead of the global optimum, and cannot improve their solution any further. We seek to improve upon the standard Particle Swarm …

Enhancing Portability In High Performance Computing: Designing Fast Scientific Code With Longevity, Jason Orender

Computer Science Theses & Dissertations

Portability, an oftentimes sought-after goal in scientific applications, confers a number of possible advantages onto computer code. Portable code will often have greater longevity, enjoy a broader ecosystem, appeal to a wider variety of application developers, and by definition will run on more systems than its pigeonholed counterpart. These advantages come at a cost, however, and a rational approach to balancing costs and benefits requires a systemic evaluation. While the benefits for each application are likely situation-dependent, the costs in terms of resources, including but not limited to time, money, computational power, and memory requirements, are quantifiable. This document will …

Two-On-One Pursuit With A Non-Zero Capture Radius, Patrick J. Wasz

Theses and Dissertations

In this paper, we revisit the "Two Cutters and Fugitive Ship" differential game that was addressed by Isaacs, but move away from point capture. We consider a two-on-one pursuit-evasion differential game with simple motion and pursuers endowed with circular capture sets of radius l > 0. The regions in the state space where only one pursuer effects the capture and the region in the state space where both pursuers cooperatively and isochronously capture the evader are characterized, thus solving the Game of Kind. Concerning the Game of Degree, the algorithm for the synthesis of the optimal state feedback strategies of the …

Optimization Of Mathematical Functions Using Gradient Descent Based Algorithms, Hala Elashmawi

Mathematics Theses

Optimization problem involves minimizing or maximizing some given quantity for certain constraints. Various real-life problems require the use of optimization techniques to find a suitable solution. These include both, minimizing or maximizing a function. The various approaches used in mathematics include methods like Linear Programming Problems (LPP), Genetic Programming, Particle Swarm Optimization, Differential Evolution Algorithms, and Gradient Descent. All these methods have some drawbacks and/or are not suitable for every scenario. Gradient Descent optimization can only be used for optimization when the goal is to find the minimum and the function at hand is differentiable and convex. The Gradient Descent …

Second-Order Generalized Differentiation Of Piecewise Linear-Quadratic Functions And Its Applications, Hong Do

Wayne State University Dissertations

The area of second-order variational analysis has been rapidly developing during the recent years with many important applications in optimization. This dissertation is devoted to the study and applications of the second-order generalized differentiation of a remarkable

class of convex extended-real-valued functions that is highly important in many aspects of nonlinear and variational analysis, specifically those related to optimization and stability.

The first goal of this dissertation is to compute the second-order subdifferential of the functions described above, which will be applied in the study of the stability of composite optimization problems associated with piecewise linear-quadratic functions, known as extended …

Optimizing Glide-Flight Paths, Rory Cveta O'Daly Maglich

Senior Projects Spring 2019

Flight is no rare event in today's society, and aviation is a global industry that significantly contributes to carbon emissions and global warming. Thus, my project theorizes how aviation might be better optimized at a fundamental level to improve aerodynamic efficiency and reduce carbon emissions. This is done by analyzing two systems of flight: gliding and powered flight. In pursuit of an understanding of a hybrid of these flight systems, I first look to qualitatively analyze the benefit of gliding over powered aviation. Powering an aircraft involves an engine that generates thrust, while gliding only involves three forces: lift, drag, …

Optimization And Control Of Arrays Of Wave Energy Converters, Jianyang Lyu

Dissertations, Master's Theses and Master's Reports

Wave Energy Converter Array is a practical approach to harvest ocean wave energy. To leverage the potential of the WEC array in terms of energy extraction, it is essential to have a properly designed array configuration and control system. This thesis explores the optimal configuration of Wave Energy Converters (WECs) arrays and their optimal control. The optimization of the WEC array allows both dimensions of individual WECs as well as the array layout to varying. In the first optimization problem, cylindrical buoys are assumed in the array where their radii and drafts are optimization parameters. Genetic Algorithms are used for …

Procuring Pediatric Vaccines In A Two-Economy Duopoly, Seongeun Lee, Susan E. Martonosi

Scripps Senior Theses

In this work, we aim to present an optimization model for vaccine pricing in a two-economy duopoly. This model observes the price dynamics between a high income country and a low income country that procure vaccinations through PAHO. This model is formulated to provide insights on optimal pricing strategy for PAHO to ultimately increase vaccine accessibility to low income countries. The objective is to satisfy the public demand at the lowest price possible, while providing enough profit for the vaccine manufacturers to stay in business. Using non-linear integer programming, the model results show that cross-subsidization occurs in PAHO vaccine procurement.

Capso: A Multi-Objective Cultural Algorithm System To Predict Locations Of Ancient Sites, Samuel Dustin Stanley

Wayne State University Dissertations

ABSTRACT

CAPSO: A MULTI-OBJECTIVE CULTURAL ALGORITHM SYSTEM TO PREDICT LOCATIONS OF ANCIENT SITES

by

SAMUEL DUSTIN STANLEY

August 2019

Advisor: Dr. Robert Reynolds

Major: Computer Science

Degree: Doctor of Philosophy

The recent archaeological discovery by Dr. John O’Shea at University of Michigan of prehistoric caribou remains and Paleo-Indian structures underneath the Great Lakes has opened up an opportunity for Computer Scientists to develop dynamic systems modelling these ancient caribou routes and hunter-gatherer settlement systems as well as the prehistoric environments that they existed in. The Wayne State University Cultural Algorithm team has been interested assisting Dr. O’Shea’s archaeological team by …

Optimization Approaches For Open-Locating Dominating Sets, Daniel Blair Sweigart

Dissertations, Theses, and Masters Projects

An Open Locating-Dominating Set (OLD set) is a subset of vertices in a graph such that every vertex in the graph has a neighbor in the OLD set and every vertex has a unique set of neighbors in the OLD set. This can also represent where sensors, capable of detecting an event occurrence at an adjacent vertex, could be placed such that one could always identify the location of an event by the specific vertices that indicated an event occurred in their neighborhood. By the open neighborhood construct, which differentiates OLD sets from identifying codes, a vertex is not able …