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
Link To Document :
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