DocumentCode :
2995497
Title :
Bounded archiving using the lebesgue measure
Author :
Knowles, Joshua D. ; Corne, David W. ; Fleischer, Mark
Author_Institution :
Dept of Chem., UMIST, Manchester, UK
Volume :
4
fYear :
2003
fDate :
8-12 Dec. 2003
Firstpage :
2490
Abstract :
Many modern multiobjective evolutionary algorithms (MOEAs) store the points discovered during optimization in an external archive, separate from the main population, as a source of innovation and/or for presentation at the end of a run. Maintaining a bound on the size of the archive may be desirable or necessary for several reasons, but choosing which points to discard and which to keep in the archive, as they are discovered, is not trivial. We briefly review the state-of-the-art in bounded archiving, and present a new method based on locally maximizing the hyper-volume dominated by the archive. The new archiver is shown to outperform existing methods, on several problem instances, with respect to the quality of the archive obtained when judged using three distinct quality measures.
Keywords :
evolutionary computation; Lebesgue measure; MOEA optimization; archive hyper-volume; bounded archiving; multiobjective evolutionary algorithm; state-of-the-art; Chemistry; Computer science; Convergence; Data structures; Educational institutions; Genetics; Modems; Physics; Systems engineering and theory; Technological innovation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2003. CEC '03. The 2003 Congress on
Print_ISBN :
0-7803-7804-0
Type :
conf
DOI :
10.1109/CEC.2003.1299401
Filename :
1299401
Link To Document :
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