Presentation 1996/7/24
A Neural Network Algorithm for the Graph Partitioning Problem
Yasuhiro Tamaki, Nobuo Funabiki, Seishi Nishikawa,
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Abstract(in English) The graph partitioning problem requires to partition the vertices of a given graph into several groups within the specified size so as to minimize the sum of the edge weights between groups. In this paper, we propose a neural network algorithm for the graph two-partitioning problem using the binary neuron model. We introduce the shaking term inthe motion equation in order to improve the solution quality. For the performance evaluation, we applied the proposed algorithm for random graphs to compare the running time and the solution quality with existing algorithms. As for solution quality, our algorithm is nearly equal to the KL algorithm, whereas as for the running time, our algorithm is much faster than the KL algorithm.
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Keyword(in English) graph partitioning problem / neural network / shaking term / KL algorithm
Paper # NC96-35
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Committee NC
Conference Date 1996/7/24(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Neural Network Algorithm for the Graph Partitioning Problem
Sub Title (in English)
Keyword(1) graph partitioning problem
Keyword(2) neural network
Keyword(3) shaking term
Keyword(4) KL algorithm
1st Author's Name Yasuhiro Tamaki
1st Author's Affiliation Division of Informatics and Mathematical Science, Graduate School of Engineering Science,Osaka University()
2nd Author's Name Nobuo Funabiki
2nd Author's Affiliation Division of Informatics and Mathematical Science, Graduate School of Engineering Science,Osaka University
3rd Author's Name Seishi Nishikawa
3rd Author's Affiliation Division of Informatics and Mathematical Science, Graduate School of Engineering Science,Osaka University
Date 1996/7/24
Paper # NC96-35
Volume (vol) vol.96
Number (no) 178
Page pp.pp.-
#Pages 8
Date of Issue