Performance comparison between a simple genetic algorithm and a Hybrid Genetic Algorithm

Author

Billy Charles Earney II

Abstract

"The Hybrid Genetic Algorithm is developed that out performs a simple genetic algorithm in almost all problems that are presented. The Hybrid Genetic Algorithm is described in detail: pseudo-code is provided for it. and for many of the operators and algorithms presented. Advance operators such as inversion, preselection, and uniform crossover are used by the Hybrid Genetic Algorithm. Simulated annealing is used to initialize the population, and hill climbing is used to search locally for a solution. Eight problems of different levels of complexity arc used to compare the simple genetic algorithm and the Hybrid Genetic Algorithm"--Abstract, page iii.

Advisor(s)

Wilkerson, Kelley R.

Committee Member(s)

Erçal, Fikret
St. Clair, Daniel C.
Dagli, Cihan H., 1949-

Department(s)

Computer Science

Degree Name

M.S. in Computer Science

Publisher

University of Missouri--Rolla

Publication Date

Spring 2000

Pagination

x, 71 pages

Note about bibliography

Includes bibliographical references (pages 69-70).

Rights

© 2000 Billy Charles Earney II, All rights reserved.

Document Type

Thesis - Restricted Access

File Type

text

Language

English

Thesis Number

T 7774

Print OCLC #

44652993

Electronic OCLC #

1113867268

Link to Catalog Record

Electronic access to the full-text of this document is restricted to Missouri S&T users. Otherwise, request this publication directly from Missouri S&T Library or contact your local library.

Recommended Citation

Earney, Billy Charles II, "Performance comparison between a simple genetic algorithm and a Hybrid Genetic Algorithm" (2000). Masters Theses. 1934.
https://scholarsmine.mst.edu/masters_theses/1934