The future of experimental research

Bartz-Beielstein T., Preuss M.


Zusammenfassung
In the experimental analysis of metaheuristic methods, two issues are still not sufficiently treated. Firstly, the performance of algorithms depends on their parametrizations-and of the parametrizations of the problem instances. However, these dependencies can be seen as means for understanding an algorithm's behavior. Secondly, the nondeterminism of evolutionary and other metaheuristic methods renders result distributions, not numbers. Based on the experience of several tutorials on the matter, we provide a comprehensive, effective, and very efficient methodology for the design and experimental analysis of metaheuristics such as evolutionary algorithms. We rely on modern statistical techniques for tuning and understanding algorithms from an experimental perspective. Therefore, we make use of the sequential parameter optimization (SPO) method that has been successfully applied as a tuning procedure to numerous heuristics for practical and theoretical optimization problems. © 2010 Springer-Verlag Berlin Heidelberg.



Publikationstyp
Buchbeitrag (Sammel-, Herausgeberband)

Begutachtet
Ja

Publikationsstatus
Veröffentlicht

Jahr
2010

Buchtitel
Experimental Methods for the Analysis of Optimization Algorithms

Herausgeber
Bartz-Beielstein T., Chiarandini M., Paquete L., Preuss M.

Erste Seite
17

Letzte Seite
49

Seiten
17-49

Band
null

Verlag
Springer Berlin Heidelberg

Sprache
Englisch

ISBN
9783642025372

DOI

Gesamter Text

Affiliierungen
Fachhochschule Koln; Universitat Dortmund