Title :
Coevolutionary Multi-Objective EAs: The Next Frontier?
Author :
Kleeman, Mark P. ; Lamont, Gary B.
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;
Conference_Titel :
Evolutionary Computation, 2006. CEC 2006. IEEE Congress on
Print_ISBN :
0-7803-9487-9
DOI :
10.1109/CEC.2006.1688516