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, leaf iii.
Tauritz, Daniel R.
Wilkerson, Ralph W.
McMillin, Bruce M.
Miller, Donald K.
Ph. D. in Computer Science
University of Missouri--Rolla
xi, 110 leaves
© 2007 Matt David Johnson, All rights reserved.
Dissertation - Citation
Library of Congress Subject Headings
Evolutionary programming (Computer science)
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Link to Catalog Record
Full-text not available: Request this publication directly from Missouri S&T Library or contact your local library.http://laurel.lso.missouri.edu/record=b6195721~S5
Johnson, Matt D., "The stored non-domination level multi-objective evolutionary algorithm" (2007). Doctoral Dissertations. 1744.