In this work we apply quasirandom sequences to develop a derivative-free algorithm for approximating the global maximum of a given function. This work is based on previous results which used a single type of quasirandom sequence in a Brute Force approach and in an approach called Localization of Search. In this work we present several methods for computing quasirandom sequences as well as measures for determining their properties. We discuss the shortcomings of the Brute Force and Localization of Search methods and then present modifications which address these issues which culminate in a new algorithm which we call Modified Localization of Search. Our algorithm is applied to a test suite of problems and the results are discussed. Finally we present some comments on code development for our algorithm. / A Thesis submitted to the Department of Scientific Computing in partial fulfillment
of the requirements for the degree of Master of Science. / Degree Awarded: Summer Semester, 2011. / Date of Defense: April 25, 2011. / Search, Sequences, Numerical, Quasirandom, Optimization / Includes bibliographical references. / Janet Peterson, Professor Directing Thesis; Max Gunzburger, Committee Member; Gordon Erlebacher, Committee Member; John Burkardt, Committee Member.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_168387 |
| Contributors | Azoulay, Ariel (authoraut), Peterson, Janet (professor directing thesis), Gunzburger, Max (committee member), Erlebacher, Gordon (committee member), Burkardt, John (committee member), Department of Scientific Computing (degree granting department), Florida State University (degree granting institution) |
| Publisher | Florida State University |
| Source Sets | Florida State University |
| Language | English, English |
| Detected Language | English |
| Type | Text, text |
| Format | 1 online resource, computer, application/pdf |
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