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Publication detail
JAROŠ, J. SCHWARZ, J.
Original Title
Parallel BMDA with an Aggregation of Probability Models
Type
conference paper
Language
English
Original Abstract
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.
Keywords
BMDA, aggregation, probability distributions, migration
Authors
JAROŠ, J.; SCHWARZ, J.
RIV year
2009
Released
20. 5. 2009
Publisher
IEEE Computational Intelligence Society
Location
Trondheim
ISBN
978-1-4244-2959-2
Book
Proceeding of 2009 IEEE Congress on Evolutionary Computation
Pages from
1683
Pages to
1690
Pages count
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/" }