Type of Document	Thesis
Author	Azoulay, Ariel
URN	etd-06132011-114745
Title	Quasirandom Optimization
Degree	Master of Science
Department	Scientific Computing, Department of
Advisory Committee	Advisor Name Title Janet Peterson Committee Chair Gordon Erlebacher Committee Member John Burkardt Committee Member Max Gunzburger Committee Member
Keywords	search sequences numerical quasirandom Optimization
Date of Defense	2011-04-25
Availability	unrestricted
Abstract 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.
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