Theses and Dissertations from UMD

Permanent URI for this communityhttp://hdl.handle.net/1903/2

New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM

More information is available at Theses and Dissertations at University of Maryland Libraries.

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    Biologically-inspired optimal control
    (2005-11-14) Shao, Cheng; Hristu, Dimitrios; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Inspired by the collective activities of ant colonies, and by their ability to gradually optimize their foraging trails, this dissertation investigates the cooperative solution of a broad class of trajectory optimization problems with various types of boundary conditions. A set of cooperative control algorithms are presented and proved to converge to an optimal solution by iteratively optimizing an initially feasible trajectory/control pair. The proposed algorithms organize a group of identical control systems by imposing a type of pair-wise interaction known as "local pursuit". The bio-inspired approach taken here requires only short-range, limited interactions between group members, avoids the need for a "global map" of the environment in which the group evolves, and solves an optimal control problem in "small" pieces, in a manner which is made precise. These features enable the application of the proposed algorithms in numerical optimization, leading to an increase of the permitting size of problems that can be solved, as well as a decrease of numerical errors incurred in ill-conditioned problems. The algorithms' effectiveness is illustrated in a series of simulations and laboratory experiments
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    An Extensible Order Promising and Revenue Management Test-bed
    (2005-05-27) Faber, Frederick Jon; Ball, Michael O; Systems Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Over the last quarter century it has become increasingly vital for large-scale businesses to exploit revenue management strategies. This is a consequence of thinning profit margins that have diminished from the effects of several pervasive trends. Among these trends are the globalization of markets, the regulation of particular industries, and, especially in the airline industry, the introduction of heightened security standards. To keep pace with this volatile landscape, revenue management and order promising policies rapidly have become more complex. Correspondingly, testing such policies has become increasingly difficult. This thesis presents an extensible test-bed designed to facilitate testing complex revenue management and order promising policies. The testbed was modeled and built using an agent-oriented architecture in order to reflect real-life business environments accurately. We describe the design and construction of the test-bed in this thesis. We then present case studies to highlight its capabilities.