Index Catalog // ScholarsArchive@OSU

Characterization and optimization of output-controllable systems

Creator:: Nandi, Arabinda Kumar, 1934-
Resource Type:: Dissertation
Full Text:: result and leads to satisfactory optimization in most cases. The principal mathematical tools used in

Two numerical methods for the solutions of optimal control problems with computed error bounds using the maximum principle of pontryagin

Creator:: Lodwick, Weldon A.
Abstract:: A simplification of the proof of the maximum principle of Pontryagin is obtained for constrained and unconstrained optimal control problems. Two numerical methods for solving optimal control problems with guaranteed error bounds using the maximum principle of Pontryagin and interval analysis are derived.
Resource Type:: Dissertation

Optimal harvesting of continuous age structured populations

Creator:: Smith, Steven J.
Abstract:: We investigate the optimal harvesting strategies for McKendrick type population models. Models of this type endow the population with a continuous age structure. They consist of a partial differential equation with a boundary condition which involves an integral of the solution. We study two problems, the first concerns the yield...
Resource Type:: Dissertation
Full Text:: (3.3), so that the techniques of control theory are more readily applicable to the optimization

Machine learning in engineering : techniques to speed up numerical optimization

Creator:: Cerbone, G. (Giuseppe)
Abstract:: Many important application problems in engineering can be formalized as nonlinear optimization tasks. However, numerical methods for solving such problems are brittle and do not scale well. For example, these methods depend critically on choosing a good starting point from which to perform the optimization search. In high-dimensional spaces, numerical...
Resource Type:: Dissertation
Full Text:: numerical optimization AN ABSTRACT OF THE THESIS OF Giuseppe Cerbone for the degree of Doctor of

Existence and uniqueness results for ℓ -optimal linear dynamic controllers for discrete time SISO systems

Creator:: Alpay, Mehmet Emin
Resource Type:: Masters Thesis
Full Text:: - OPTIMIZATION PROBLEM 15 Mathematical Preliminaries II 15 l'- optimization Problem 17 Construction of

Optimization of machine allocation in RingLeader

Creator:: King, Jonathan B.
Abstract:: Many different types of distributed batch scheduling systems have been developed in the last decade to take advantage of the decentralization of computers and the enormous investments that many companies and educational institutions have in desktop workstations. Based on the premise that the majority of desktop workstations are significantly underutilized,...
Resource Type:: Masters Thesis
Full Text:: Master of Science in Computer Science presented on December 6, 1996. Title: Optimization of Machine

Accuracy versus cost in distributed data mining

Creator:: Deutschman, Stephanie
Abstract:: A basic tradeoff to consider when designing a distributed data-mining framework is the need for a compromise between the cost of communication and computation resources and the accuracy of the mining results. This is essentially a decision of whether it is more efficient to communicate all of the data to...
Resource Type:: Masters Thesis
Full Text:: and some mathematical transformations it can be established that an optimization problem

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

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

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

ScholarsArchive@OSU

Characterization and optimization of output-controllable systems

Two numerical methods for the solutions of optimal control problems with computed error bounds using the maximum principle of pontryagin

Optimal harvesting of continuous age structured populations

Machine learning in engineering : techniques to speed up numerical optimization

Existence and uniqueness results for ℓ -optimal linear dynamic controllers for discrete time SISO systems

Optimization of machine allocation in RingLeader

Accuracy versus cost in distributed data mining

Bayesian methods for knowledge transfer and policy search in reinforcement learning

Bayesian optimization with empirical constraints

Bi-criteria group scheduling with learning in hybrid flow shops

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