The stored non-domination level multi-objective evolutionary algorithm

Author

Matt D. Johnson

Abstract

"The research presented in this dissertation is in the field of Multi-Objective Evolutionary Algorithms. Evolutionary Algorithms (EAs) are a class of algorithms which model Darwin's theory of evolution to search for solutions to difficult problems. Multi-Objective Evolutionary Algorithms (MOEAs) are a broader case of the standard EA. The primary distinction between an EA and a MOEA is that and EA searches for a single solution based on one objective, while a MOEA searches for a set of solutions based on a number of different objectives. The heart of this research is a new algorithm call SNDL-MOEA, which stands for "Stored Non-Domination Level Multi-Objective Evolutionary Algorithm"--Abstract, page iii.

Advisor(s)

Tauritz, Daniel R.
Wilkerson, Ralph W.

Committee Member(s)

Leopold, Jennifer
McMillin, Bruce M.
Miller, Donald K.

Department(s)

Computer Science

Degree Name

Ph. D. in Computer Science

Publisher

University of Missouri--Rolla

Publication Date

Spring 2007

Pagination

xi, 110 pages

Note about bibliography

Includes bibliographical references (pages 105-109).

Rights

© 2007 Matt David Johnson, All rights reserved.

Document Type

Dissertation - Citation

File Type

text

Language

English

Subject Headings

Computer musicEvolutionary programming (Computer science)Genetic algorithms

Thesis Number

T 9186

Print OCLC #

190952628

Recommended Citation

Johnson, Matt D., "The stored non-domination level multi-objective evolutionary algorithm" (2007). Doctoral Dissertations. 1744.
https://scholarsmine.mst.edu/doctoral_dissertations/1744