Detail publikace

Evolutionary Multiobjective Bayesian Optimization Algorithm:Experimental Study

SCHWARZ, J., OČENÁŠEK, J.

Originální název

Evolutionary Multiobjective Bayesian Optimization Algorithm:Experimental Study

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

This paper deals with the utilizing of the Bayesian optimization algorithm (BOA) for multiobjective optimization of hypergraph partitioning. The main attention is focused on the incorporation of the Pareto optimality concept. We have modified the standard algorithm BOA for one criterion optimization according to well known niching techniques to find the Pareto optimal set. This approach was compared with standard weighting techniques and the single optimization approach with the constraint. The experiments are focused mainly on the bi-objective optimization because of the visualization simplicity.

Klíčová slova

Multiobjective optimization, evolutionary algorithms, Bayesian optimization algorithm, Pareto set, niching techniques, hypergraph bisectioning

Autoři

SCHWARZ, J., OČENÁŠEK, J.

Rok RIV

2001

Vydáno

1. 1. 2001

Místo

Hradec nad Moravicí

ISBN

80-85988-57-7

Kniha

Proceedings of the 35th Spring International Conference MOSIS'01, Vol. 1

Strany od

101

Strany do

108

Strany počet

8

URL

http://www.fit.vutbr.cz/~schwarz/PDFCLANKY/mosis01.pdf

BibTex

@inproceedings{BUT5431,
  author="Josef {Schwarz} and Jiří {Očenášek}",
  title="Evolutionary Multiobjective Bayesian Optimization Algorithm:Experimental Study",
  booktitle="Proceedings of the 35th Spring International Conference MOSIS'01, Vol. 1",
  year="2001",
  pages="101--108",
  address="Hradec nad Moravicí",
  isbn="80-85988-57-7",
  url="http://www.fit.vutbr.cz/~schwarz/PDFCLANKY/mosis01.pdf"
}