Publication Details

Bayesian Optimization Algorithms for Dynamic Problems

KOBLIHA, M.; SCHWARZ, J.; OČENÁŠEK, J. Bayesian Optimization Algorithms for Dynamic Problems. In Applications of Evolutionary Computing. Lecture Notes in Computer Science. Budapest: Springer Verlag, 2006. p. 800-804. ISBN: 3-540-33237-5. ISSN: 0302-9743.

Czech title

Bayesovské optimalizační algoritmy pro dynamické problémy

Type

conference paper

Language

English

Authors

Kobliha Miloš, Ing.
Schwarz Josef, doc. Ing., CSc. (CM-SFE)
Očenášek Jiří, Ing.

Keywords

BOA algorithm, dynamic problem, optimalization

Abstract

This paper is an experimental study investigating the capability of Bayesian optimization algorithms to solve dynamic problems. We tested the performance of two variants of Bayesian optimization algorithms - Mixed continuous-discrete Bayesian Optimization Algorithm (MBOA), Adaptive Mixed Bayesian Optimization Algorithm (AMBOA) - and new proposed modifications with embedded Sentinels concept and Hypervariance. We have compared the performance of these variants on a simple dynamic problem - a time-varying function with predefined parameters. The experimental results confirmed the benefit of Sentinels concept and Hypervariance embedded into MBOA algorithm for tracking a moving optimum.

Published

2006

Pages

800–804

Journal

Lecture Notes in Computer Science, vol. 2006, no. 3907, ISSN 0302-9743

Proceedings

Applications of Evolutionary Computing

ISBN

3-540-33237-5

Publisher

Springer Verlag

Place

Budapest

BibTeX

@inproceedings{BUT22416,
  author="Miloš {Kobliha} and Josef {Schwarz} and Jiří {Očenášek}",
  title="Bayesian Optimization Algorithms for Dynamic Problems",
  booktitle="Applications of Evolutionary Computing",
  year="2006",
  journal="Lecture Notes in Computer Science",
  volume="2006",
  number="3907",
  pages="800--804",
  publisher="Springer Verlag",
  address="Budapest",
  isbn="3-540-33237-5",
  issn="0302-9743"
}