Stopping Criteria for Multimodal Optimization

Wessing S, Preuss M, Trautmann H


Zusammenfassung
Multimodal optimization requires maintenance of a good search space coverage and approximation of several optima at the same time. We analyze two constitutive optimization algorithms and show that in many cases, a phase transition occurs at some point, so that either diversity collapses or optimization stagnates. But how to derive suitable stopping criteria for multimodal optimization? Experimental results indicate that an algorithm’s population contains sufficient information to estimate the point in time when several performance indicators reach their optimum. Thus, stopping criteria are formulated based on summary characteristics employing objective values and mutation strength.

Schlüsselwörter
Multimodal optimization; global optimization; multiobjective selection; convergence detection; stopping criteria



Publikationstyp
Aufsatz (Konferenz)

Begutachtet
Ja

Publikationsstatus
Veröffentlicht

Jahr
2014

Konferenz
Parallel Problem Solving from Nature - PPSN XIII

Konferenzort
Ljubljana, Slovenia

Herausgeber
Bartz-Beielstein T, Branke J, Filipic B, Smith J

Seiten
141-150

Band
8672

Reihe
Lecture Notes in Computer Science

Verlag
Springer

Sprache
Englisch

DOI

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