Doctoral Dissertations

The stored non-domination level multi-objective evolutionary algorithm


"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.


Tauritz, Daniel R.
Wilkerson, Ralph W.

Committee Member(s)

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


Computer Science

Degree Name

Ph. D. in Computer Science


University of Missouri--Rolla

Publication Date

Spring 2007


xi, 110 pages

Note about bibliography

Includes bibliographical references (pages 105-109).


© 2007 Matt David Johnson, All rights reserved.

Document Type

Dissertation - Citation

File Type




Subject Headings

Computer music
Evolutionary programming (Computer science)
Genetic algorithms

Thesis Number

T 9186

Print OCLC #


Link to Catalog Record

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