Detail publikace

A PROBLEM KNOWLEDGE BASED BAYESIAN OPTIMIZATION ALGORITHM APPLIED IN MULTIPROCESSOR SCHEDULING

SCHWARZ Josef a JAROŠ Jiří. A PROBLEM KNOWLEDGE BASED BAYESIAN OPTIMIZATION ALGORITHM APPLIED IN MULTIPROCESSOR SCHEDULING. In: Mendel Conference on Soft Computing. Brno: Fakulta strojního inženýrství VUT, 2004, s. 83-88. ISBN 80-214-2676-4.
Název česky
Znalostně orientovaný Bayesovský optimalizační algoritmus
Typ
článek ve sborníku konference
Jazyk
angličtina
Autoři
Schwarz Josef, doc. Ing., CSc. (UPSY FIT VUT)
Jaroš Jiří, doc. Ing., Ph.D. (UPSY FIT VUT)
Abstrakt

This paper deals with the multiprocessor scheduling problem, which  belongs to the class of frequently solved decomposition tasks. The goals is to experimentally compare the performance of the recently proposed Mixed Bayesian Optimization Algorithm (MBOA) based on probabilistic model with  the newly derived  knowledge  based MBOA version (KMBOA) This algorithm includes  utilization of prior knowledge about the structure of a task graph to speed-up the  convergence  and the  solution quality. The performance of standard  genetic algorithm was also tested on the same benchmarks.

Rok
2004
Strany
83-88
Sborník
Mendel Conference on Soft Computing
Konference
Tenth International Mendel Conference on Soft Computing, FME, VUT BRNO, CZ
ISBN
80-214-2676-4
Vydavatel
Fakulta strojního inženýrství VUT
Místo
Brno, CZ
BibTeX 
@INPROCEEDINGS{FITPUB7519,
   author = "Josef Schwarz and Ji\v{r}\'{i} Jaro\v{s}",
   title = "A PROBLEM KNOWLEDGE BASED BAYESIAN OPTIMIZATION ALGORITHM APPLIED IN MULTIPROCESSOR SCHEDULING",
   pages = "83--88",
   booktitle = "Mendel Conference on Soft Computing",
   year = 2004,
   location = "Brno, CZ",
   publisher = "Faculty of Mechanical Engineering BUT",
   ISBN = "80-214-2676-4",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/7519"
}
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