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Theses/Dissertations

Optimization

2016

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Articles 1 - 14 of 14

Full-Text Articles in Physical Sciences and Mathematics

Improved 2d And 3d Resistivity Surveys Using Buried Electrodes And Optimized Arrays: The Multi-Electrode Resistivity Implant Technique (Merit), Henok Gidey Kiflu Nov 2016

Improved 2d And 3d Resistivity Surveys Using Buried Electrodes And Optimized Arrays: The Multi-Electrode Resistivity Implant Technique (Merit), Henok Gidey Kiflu

USF Tampa Graduate Theses and Dissertations

This thesis presents a novel resistivity method called Multi-Electrode resistivity technique (MERIT) that is used for high resolution imaging of complex geologic features at depth and near the edges of survey lines. The MERIT electrodes are especially shaped and designed to be self-driven using a robust-direct push technique. Measurements are taken using optimized arrays that are generated using a modified version of the “Compare-R” optimization algorithm. This work focused on both two-dimensional (MERIT2D) and three-dimensional (MERIT3D) applications of the buried array and show the relevance of the additional information gained by the addition of deep electrodes especially in sites with …


Achieving High Reliability And Efficiency In Maintaining Large-Scale Storage Systems Through Optimal Resource Provisioning And Data Placement, Lipeng Wan Aug 2016

Achieving High Reliability And Efficiency In Maintaining Large-Scale Storage Systems Through Optimal Resource Provisioning And Data Placement, Lipeng Wan

Doctoral Dissertations

With the explosive increase in the amount of data being generated by various applications, large-scale distributed and parallel storage systems have become common data storage solutions and been widely deployed and utilized in both industry and academia. While these high performance storage systems significantly accelerate the data storage and retrieval, they also bring some critical issues in system maintenance and management. In this dissertation, I propose three methodologies to address three of these critical issues.

First, I develop an optimal resource management and spare provisioning model to minimize the impact brought by component failures and ensure a highly operational experience …


A Multi-Objective Approach To Tactical Maneuvering Within Real Time Strategy Games, Christopher D. Ball Jun 2016

A Multi-Objective Approach To Tactical Maneuvering Within Real Time Strategy Games, Christopher D. Ball

Theses and Dissertations

The real time strategy (RTS) environment is a strong platform for simulating complex tactical problems. The overall research goal is to develop artificial intelligence (AI) RTS planning agents for military critical decision making education. These agents should have the ability to perform at an expert level as well as to assess a players critical decision-making ability or skill-level. The nature of the time sensitivity within the RTS environment creates very complex situations. Each situation must be analyzed and orders must be given to each tactical unit before the scenario on the battlefield changes and makes the decisions no longer relevant. …


A General Framework Of Large-Scale Convex Optimization Using Jensen Surrogates And Acceleration Techniques, Soysal Degirmenci May 2016

A General Framework Of Large-Scale Convex Optimization Using Jensen Surrogates And Acceleration Techniques, Soysal Degirmenci

McKelvey School of Engineering Theses & Dissertations

In a world where data rates are growing faster than computing power, algorithmic acceleration based on developments in mathematical optimization plays a crucial role in narrowing the gap between the two. As the scale of optimization problems in many fields is getting larger, we need faster optimization methods that not only work well in theory, but also work well in practice by exploiting underlying state-of-the-art computing technology.

In this document, we introduce a unified framework of large-scale convex optimization using Jensen surrogates, an iterative optimization method that has been used in different fields since the 1970s. After this general treatment, …


Improving Ventricular Catheter Design Through Computational Fluid Dynamics, Sofy Hefets Weisenberg May 2016

Improving Ventricular Catheter Design Through Computational Fluid Dynamics, Sofy Hefets Weisenberg

Masters Theses

Cerebrospinal fluid (CSF) shunts are fully implantable medical devices that are used to treat patients suffering from conditions characterized by elevated intracranial pressure, such as hydrocephalus. In cases of shunt failure or malfunction, patients are often required to endure one or more revision surgeries to replace all or part of the shunt. One of the primary causes of CSF shunt failure is obstruction of the ventricular catheter, a component of the shunt system implanted directly into the brain's ventricular system. This work aims to improve the design of ventricular catheters in order to reduce the incidence of catheter obstruction and …


An Optimized Multiple Right-Hand Side Dslash Kernel For Intel Xeon Phi, Aaron Walden Apr 2016

An Optimized Multiple Right-Hand Side Dslash Kernel For Intel Xeon Phi, Aaron Walden

Computer Science Theses & Dissertations

Lattice quantum chromodynamics (LQCD) stands unique as the only computationally tractable, non-perturbative, and model-independent quantum field theory of the strong nuclear force. The computational core of LQCD is the Wilson Dslash operator, a nearest neighbor stencil operator summing matrix-vector multiplications over lattice points, whose performance is bandwidth-bound on most architectures. Reportedly, up to 90\% of LQCD running time may be spent computing Dslash. In recent years, efforts have been made by researchers to optimize LQCD calculations for floating point coprocessor cards such as GPUs and Intel Xeon Phi Knights Corner (KNC), which boast powerful vector processing units. Most of these …


Enabling Optimizations Through Demodularization, Blake Dennis Johnson Mar 2016

Enabling Optimizations Through Demodularization, Blake Dennis Johnson

Theses and Dissertations

Programmers want to write modular programs to increase maintainability and create abstractions, but modularity hampers optimizations, especially when modules are compiled separately or written in different languages. In languages with syntactic extension capabilities, each module in a program can be written in a separate language, and the module system must ensure that the modules interoperate correctly. In Racket, the module system ensures this by separating module code into phases for runtime and compile-time and allowing phased imports and exports inside modules. We present an algorithm, called demodularization, that combines all executable code from a phased modular program into a single …


Probability Models For Health Care Operations With Application To Emergency Medicine, Azaz Bin Sharif Feb 2016

Probability Models For Health Care Operations With Application To Emergency Medicine, Azaz Bin Sharif

Electronic Thesis and Dissertation Repository

This thesis consists of four contributing chapters; two of which are inspired by practical problems related to emergency department (ED) operations management and the remaining two are motivated by the theoretical problem related to the time-dependent priority queue. Unlike classical priority queue, priorities in the time-dependent priority queue depends on the amount of time an arrival waits for service in addition to the priority class they belong. The mismatch between the demand for ED services and the available resources have direct and indirect negative consequences. Moreover, ED physician pay in some jurisdictions reflects pay-for-performance contracts based on operational benchmarks. To …


A Comparative Analysis Of An Interior-Point Method And A Sequential Quadratic Programming Method For The Markowitz Portfolio Management Problem, Zhifu Xiao Jan 2016

A Comparative Analysis Of An Interior-Point Method And A Sequential Quadratic Programming Method For The Markowitz Portfolio Management Problem, Zhifu Xiao

Honors Papers

In this paper, I give a brief introduction of the general optimization problem as well as the convex optimization problem. The portfolio selection problem, as a typical type of convex optimization problem, can be easily solved in polynomial time. However, when the number of available stocks in the portfolio becomes large, there might be a significant difference in the running time of different polynomial-time solving methods. In this paper, I perform a comparative analysis of two different solving methods and discuss the characteristics and differences.


Enhanced Pump Schedule Optimization For Large Water Distribution Networks To Maximize Environmental And Economic Benefits, Seyed Mohsen Sadatiyan Abkenar Jan 2016

Enhanced Pump Schedule Optimization For Large Water Distribution Networks To Maximize Environmental And Economic Benefits, Seyed Mohsen Sadatiyan Abkenar

Wayne State University Dissertations

For more than four decades researchers tried to develop optimization method and tools to reduce electricity consumption of pump stations of water distribution systems. Based on this ongoing research trend, about a decade ago, some commercial pump operation optimization software introduced to the market. Using metaheuristic and evolutionary techniques (e.g. Genetic Algorithm) make some commercial and research tools able to optimize the electricity cost of small water distribution systems (WDS). Still reducing the environmental footprint of these systems and dealing with large and complicated water distribution system is a challenge.

In this study, we aimed to develop a multiobjective optimization …


Optimizing Vehicle Usage Using Csp, Sat And Max-Sat, Raheem T. Al Rammahi Jan 2016

Optimizing Vehicle Usage Using Csp, Sat And Max-Sat, Raheem T. Al Rammahi

Electronic Theses and Dissertations

Most of the companies in Iraq spend significant amounts of time and money when transferring employees between home and work. In this thesis, we model the problem of the Dhi Qar Oil company (DQOC) transportations using three modeling languages from AI: Constraint Programing (CP), Boolean Satisfiability (SAT), and Maximum Satisfiability (MAX-SAT). We then use solvers to find optimal solutions to this problem.

We show which of these solvers is more efficient when finding optimal solutions. For this purpose, we create a test suite of 360 problems to test these solvers. All solvers are applied to these problems and the final …


Optimal Control And Its Application To The Life-Cycle Savings Problem, Tracy A. Taylor Jan 2016

Optimal Control And Its Application To The Life-Cycle Savings Problem, Tracy A. Taylor

Theses and Dissertations

Throughout the course of this thesis, we give an introduction to optimal control theory and its necessary conditions, prove Pontryagin's Maximum Principle, and present the life-cycle saving under uncertain lifetime optimal control problem. We present a very involved sensitivity analysis that determines how a change in the initial wealth, discount factor, or relative risk aversion coefficient may affect the model the terminal depletion of wealth time, optimal consumption path, and optimal accumulation of wealth path. Through simulation of the life-cycle saving under uncertain lifetime model, we are not only able to present the model dynamics through time, but also to …


Mechanisms For Improving Information Quality In Smartphone Crowdsensing Systems, Francesco Restuccia Jan 2016

Mechanisms For Improving Information Quality In Smartphone Crowdsensing Systems, Francesco Restuccia

Doctoral Dissertations

"Given its potential for a large variety of real-life applications, smartphone crowdsensing has recently gained tremendous attention from the research community. Smartphone crowdsensing is a paradigm that allows ordinary citizens to participate in large-scale sensing surveys by using user-friendly applications installed in their smartphones. In this way, fine-grained sensing information is obtained from smartphone users without employing fixed and expensive infrastructure, and with negligible maintenance costs.

Existing smartphone sensing systems depend completely on the participants' willingness to submit up-to-date and accurate information regarding the events being monitored. Therefore, it becomes paramount to scalably and effectively determine, enforce, and optimize the …


The New Issues In Classification Problems, Md Mahmudul Hasan Jan 2016

The New Issues In Classification Problems, Md Mahmudul Hasan

Open Access Theses & Dissertations

The data involved with science and engineering getting bigger everyday. To study and organize a big amount of data is difficult without classification. In machine learning, classification is the problem of identifying a given data from a set of categories. There are several classification technique people using to classify a given data. In our work we present a sparse representation technique to perform classification. The popularity of this technique motivates us to use on our collected samples. To find a sparse representation, we used an $l_1$-minimization algorithm which is a convex relaxation algorithm proven very efficient by researchers. The purpose …