Improved topological niching for real-valued global optimization

Preuss M.


Zusammenfassung
We show how nearest-better clustering, the core component of the NBC-CMA niching evolutionary algorithm, is improved by appyling a second heuristic rule. This leads to enhanced basin identification for higher dimensional (5D to 20D) optimization problems, where the NBC-CMA has previously shown only mediocre performance compared to other niching and global optimization algorithms. The new method is integrated into a niching algorithm (NEA2) and compared to NBC-CMA and BIPOP-CMA-ES via the BBOB benchmarking suite. It performs very well on problems that enable recognizing basins at all with reasonable effort (number of basins not too high, e.g. the Gallagher problems), as expected. Beyond that point, niching is obviously not applicable any more and random restarts as done by the CMA-ES are the method of choice. © 2012 Springer-Verlag.



Publikationstyp
Aufsatz (Konferenz)

Begutachtet
Ja

Publikationsstatus
Veröffentlicht

Jahr
2012

Konferenz
EvoCOMNET, EvoCOMPLEX, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoNUM, EvoPAR, EvoRISK, EvoSTIM, and EvoSTOC, EvoApplications 2012

Konferenzort
Malaga, esp

Erste Seite
386

Letzte Seite
395

Seiten
386-395

Band
null

Reihe
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Sprache
Englisch

ISSN
1611-3349

ISBN
9783642291777

DOI

Gesamter Text

Affiliierungen
Universitat Dortmund