DocumentCode
2463780
Title
Coevolutionary Multi-Objective EAs: The Next Frontier?
Author
Kleeman, Mark P. ; Lamont, Gary B.
fYear
2006
fDate
16-21 July 2006
Firstpage
1726
Lastpage
1735
Abstract
Multi-objective Evolutionary Algorithms (MOEAs) have become useful for solving many real world problems that have multiple objectives that need to be optimized. An area of research that is still in its infancy is the application of coevolutionary techniques to MOEAs. Recently a few researchers have explored the idea of combining coevolution with MOEAs. This paper discusses these researchers’ concepts in the field of Coevolutionary MOEAs (CMOEA). Their work is summarized and categorized based on how coevolution is applied to the MOEA. Additionally, some potential developments of coevolution integrated with MOEAs is addressed and we describe situations in which they might be most beneficial.
Keywords
Aggregates; Dictionaries; Evolutionary computation; Genetic algorithms; Round robin; Sorting; Symbiosis;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2006. CEC 2006. IEEE Congress on
Print_ISBN
0-7803-9487-9
Type
conf
DOI
10.1109/CEC.2006.1688516
Filename
1688516
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