DagSemProc.09181.5.pdf
- Filesize: 2.18 MB
- 32 pages
Document
Sequential Parameter Optimization
Author
-
Part of:
Volume:
Dagstuhl Seminar Proceedings, Volume 9181
Series: Dagstuhl Seminar Proceedings (DagSemProc) - License:
Creative Commons Attribution 4.0 International license
- Publication date: 2009-07-30
Cite AsGet BibTex
Thomas Bartz-Beielstein. Sequential Parameter Optimization. In Sampling-based Optimization in the Presence of Uncertainty. Dagstuhl Seminar Proceedings, Volume 9181, pp. 1-32, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2009)
https://doi.org/10.4230/DagSemProc.09181.5
https://doi.org/10.4230/DagSemProc.09181.5
Abstract
We provide a comprehensive, effective and very efficient methodology for the design and experimental analysis of 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.
Two case studies, which illustrate the applicability of SPO to algorithm tuning
and model selection, are presented.
Keywords
- Optimization
- evolutionary algorithms
- design of experiments
Metrics
- Access Statistics
-
Total Accesses (updated on a weekly basis)
0PDF Downloads