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  • Bayesian optimization with empirical constraints

    Creator:
    Azimi, Javad
    Abstract:
    Bayesian Optimization (BO) methods are often used to optimize an unknown function f(•) that is costly to evaluate. They typically work in an iterative manner. In each iteration, given a set of observation points, BO algorithms select k ≥ 1 points to be evaluated. The results of those points are...
    Resource Type:
    Dissertation
    Full Text:
    : Bayesian Optimization with Empirical Constraints Abstract approved: Xiaoli Z. Fern Bayesian Optimization

  • Learning greedy policies for the easy-first framework

    Creator:
    Xie, Jun
    Abstract:
    Easy-first, a search-based structured prediction approach, has been applied to many NLP tasks including dependency parsing and coreference resolution. This approach employs a learned greedy policy (action scoring function) to make easy decisions first, which constrains the remaining decisions and makes them easier. This thesis studies the problem of learning...
    Resource Type:
    Masters Thesis
    Full Text:
    and principled online learn- ing algorithm that solves an optimization problem to update the weights

  • Floating Offshore Wind Array Systems Optimization off the US West Coast using an Extended Pattern Search Algorithm

    Creator:
    Forinash, Caitlin P.
    Abstract:
    The large wind resource off the United States West Coast has the potential to generate wind power for millions of homes, yet the high cost of energy for offshore wind power compared to traditional sources has slowed the development of offshore wind farms in the US. The four studies presented...
    Resource Type:
    Masters Thesis
    Full Text:
    : Floating Offshore Wind Array Systems Optimization off the US West Coast using an Extended Pattern Search

  • Bi-criteria group scheduling with learning in hybrid flow shops

    Creator:
    Bozorgirad, Mir Abbas
    Abstract:
    In this research, a bi-criteria group scheduling problem is investigated in hybrid flow shop (HFS) environments, where the parallel machines in each stage are unrelated, meaning not identical. The objective of the problem is to minimize a linear combination of the total weighted completion times as a means of complying...
    Resource Type:
    Dissertation
    Full Text:
    ................................................................................................................ 19 4.1. Mathematical programming model

  • Wave Energy Converter Array Optimization : Array Economic Analysis and Preliminary Results of a Genetic Algorithm Approach Introducing Cost Factors

    Creator:
    Sharp, Christopher J.
    Abstract:
    With the need to integrate renewable energy sources into the current energy portfolio and the proximity of many population centers to an ocean coastline, it is pressing that marine energy systems, specifically wave energy converters (WECs), are evaluated as potential solutions for meeting energy needs. In order to best understand...
    Resource Type:
    Masters Thesis
    Full Text:
    Wave Energy Converter Array Optimization: Array Economic

  • Multi-Objective Optimization in Multiagent Systems

    Creator:
    Yliniemi, Logan Michael
    Abstract:
    Cooperative multiagent systems are used as solution concepts in many application domains including air traffic control, satellite communications, and extra planetary exploration. As systems become more distributed and complex, we observe three phenomena. First, these systems cannot be accurately modeled, rendering traditional model based control methods inadequate. Second, system parameters...
    Resource Type:
    Dissertation
    Full Text:
    , 2015. Title: Multi-Objective Optimization in Multiagent Systems Abstract approved: Kagan Tumer

  • A comparison of single runs versus multistart for simulated annealing and threshold accepting

    Creator:
    Crews, Matthew
    Abstract:
    Simulated Annealing and Threshold Accepting are two stochastic search algorithms that have been successfully used on a variety of complex and difficult problem sets. Due to their stochastic nature they are not guaranteed to produce the same result for each run. This means that these techniques actually produce a distribution...
    Resource Type:
    Masters Thesis
    Full Text:
    optimization algorithms. Thanks must also be extended to Dr. Hector Vergara and Dr. Guanyi Lu who made

  • Bayesian methods for knowledge transfer and policy search in reinforcement learning

    Creator:
    Wilson, Aaron
    Abstract:
    How can an agent generalize its knowledge to new circumstances? To learn effectively an agent acting in a sequential decision problem must make intelligent action selection choices based on its available knowledge. This dissertation focuses on Bayesian methods of representing learned knowledge and develops novel algorithms that exploit the represented...
    Resource Type:
    Dissertation
    Full Text:
    problem of generalizing knowledge gained from previously-executed policies. Bayesian Optimization is a

  • Mathematical treatment and simulation of methane hydrates and adsorption models

    Creator:
    Medina, Francis Patricia
    Abstract:
    In this dissertation we develop mathematical treatment for two important applications: (i) evolution of methane in coalbeds with the associated phenomena of adsorption, and (ii) formation of methane hydrates in seabed. We use simplified models for (i) and (ii) since we are more interested in qualitative properties of the solutions...
    Resource Type:
    Dissertation
    Full Text:
    Mathematical Treatment and Simulation of Methane Hydrates

  • Machine Learning Methods for Computational Sustainability

    Creator:
    Liu, Liping
    Abstract:
    Maintaining the sustainability of the earth’s ecosystems has attracted much attention as these ecosystems are facing more and more pressure from human activities. Machine learning can play an important role in promoting sustainability as a large amount of data is being collected from ecosystems. There are at least three important...
    Resource Type:
    Dissertation
    Full Text:
    the formulation with two optimization algorithms. The learning techniques in this thesis are general