Conference paper

SCHWARZ Josef and OČENÁŠEK Jiří. The knowledge-based evolutionary algorithm KBOA for hypergraph bisectioning. In: Proceedings of the Fourth Joint Conference on Knowledge-Based Software Engineering Brno, Czech Republic, 2000. BRNO: IOS Press, 2000, pp. 51-58. ISBN 1-58603-060-4.
Publication language:english
Original title:A problem knowledge-based evolutionary algorithm KBOA for hypergraph bisectioning
Pages:51-58
Proceedings:Proceedings of the Fourth Joint Conference on Knowledge-Based Software Engineering Brno, Czech Republic, 2000
Conference:IEEE Design and Diagnostics of Electronic Circuits and Systems 2002
Place:BRNO, CZ
Year:2000
ISBN:1-58603-060-4
Publisher:IOS Press
URL:http://www.fit.vutbr.cz/~schwarz/PDFCLANKY/jckbse.ps [PS]
Keywords
problem knowledge, Bayesian evolutionary algorithm, hypergraph partitioning
Annotation
This paper is an experimental study on an utilization of additional knowledge about the decomposition problem to be solved. We have demonstrated this approach on the hypergraph bisectioning that can serve as a model of system decomposition in common, data base decomposition etc. We have focused on the extension of the Bayesian Optimization Algorithm BOA. The extension of the original BOA algorithm is based on the usage of a prior information about the hypergraph structure. This knowledge is used for both setting initial Bayesian network and the initial population using injection of clusters to improve the convergence of the decomposition process. The behaviour of our version KBOA is tested on the set of benchmarks, such as grid and random geometric graphs as well as real hypergraphs.
Abstract
This paper is an experimental study on an utilization of additional knowledge about the decomposition problem to be solved. We have demonstrated this approach on the hypergraph bisectioning that can serve as a model of system decomposition in common, data base decomposition etc. We have focused on the extension of the Bayesian Optimization Algorithm BOA. The extension of the original BOA algorithm is based on the usage of a prior information about the hypergraph structure. This knowledge is used for both setting initial Bayesian network and the initial population using injection of clusters to improve the convergence of the decomposition process. The behaviour of our version KBOA is tested on the set of benchmarks, such as grid and random geometric graphs as well as real hypergraphs.
BibTeX:
@INPROCEEDINGS{
   author = {Josef Schwarz and Ji{\v{r}}{\'{i}}
	O{\v{c}}en{\'{a}}{\v{s}}ek},
   title = {A problem knowledge-based evolutionary algorithm KBOA for
	hypergraph bisectioning},
   pages = {51--58},
   booktitle = {Proceedings of the Fourth Joint Conference on
	Knowledge-Based Software Engineering Brno, Czech Republic,
	2000},
   year = {2000},
   location = {BRNO, CZ},
   publisher = {IOS Press},
   ISBN = {1-58603-060-4},
   language = {english},
   url = {http://www.fit.vutbr.cz/research/view_pub.php?id=6435}
}

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