Author Type

Graduate Student

Date of Award

1995

Document Type

Thesis

Publication Status

Version of Record

Submission Date

October 2026

Thesis/Dissertation Advisor [Chair]

Zhuang, Hanqi

Abstract

Research and applications of genetic algorithms have become increasingly important in a wide variety of scientific fields. In this thesis, we present an empirical analysis of genetic algorithms in the function optimization area. As a focus of our research, a novel empirical analysis approach to various genetic algorithms is provided. The research starts from the survey of current trends in genetic algorithms, followed by exploring the characteristics of the simple genetic algorithm, the modified genetic algorithm and hybridized genetic algorithm. A number of typical function optimization problems are solved by these genetic algorithms. Ample empirical data associated with various modifications to the simple genetic algorithm is also provided. Results from this research can be used to assist practitioners in their applications of genetic algorithms.

Extent

138 p.

Comments

College of Engineering and Computer Science|FAU Electronic Theses and Dissertations Collection|Thesis (M.S.E.)--Florida Atlantic University, 1995.|College of Engineering and Computer Science

Identifier

FADT15210

Format

pdf

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