Detail publikace

Parallel BMDA with an Aggregation of Probability Models

JAROŠ, J. SCHWARZ, J.

Originální název

Parallel BMDA with an Aggregation of Probability Models

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

The paper is focused on the problem of aggregation of probability distribution applicable for parallel Bivariate Marginal Distribution Algorithm (pBMDA). A new approach based 000274803100222on quantitative combination of probabilistic models is presented. Using this concept, the traditional migration of individuals is replaced with a newly proposed technique of probability parameter migration. In the proposed strategy, the adaptive learning of the resident probability model is used. The short theoretical study is completed by an experimental works for the implemented parallel BMDA algorithm (pBMDA). The performance of pBMDA algorithm is evaluated for various problem size (scalability) and interconnection topology. In addition, the comparison with the previously published aBMDA  is presented.

Klíčová slova

BMDA, aggregation, probability distributions, migration

Autoři

JAROŠ, J.; SCHWARZ, J.

Rok RIV

2009

Vydáno

20. 5. 2009

Nakladatel

IEEE Computational Intelligence Society

Místo

Trondheim

ISBN

978-1-4244-2959-2

Kniha

Proceeding of 2009 IEEE Congress on Evolutionary Computation

Strany od

1683

Strany do

1690

Strany počet

8

URL

https://www.fit.vut.cz/research/publication/8948/

BibTex

@inproceedings{BUT33724,
  author="Jiří {Jaroš} and Josef {Schwarz}",
  title="Parallel BMDA with an Aggregation of Probability Models",
  booktitle="Proceeding of 2009 IEEE Congress on Evolutionary Computation",
  year="2009",
  pages="1683--1690",
  publisher="IEEE Computational Intelligence Society",
  address="Trondheim",
  isbn="978-1-4244-2959-2",
  url="https://www.fit.vut.cz/research/publication/8948/"
}