Presentation 2003/6/16
A Theoretical Study on A Neural Method for Combinatorial Optimization Problems
Keiichi SATO, Tohru IKEGUCHI,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) We have already proposed a new observation function for deciding output values of the chaotic neural network (CNN) for solving quadratic assignment problems. According to the observation function, we have shown that one can obtain good solutions, since the method always offers feasible solutions. In this paper, we theoretically investigate the solving performance of the novel observation function by comparing two conventional observation functions. We prove that a set of feasible solutions with the novel observation function includes those of the conventional observation functions.
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Keyword(in English) Chaotic Neural Network / Quadratic Assignment Problems / Observation Function
Paper # NLP2003-16
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Conference Information
Committee NLP
Conference Date 2003/6/16(1days)
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Paper Information
Registration To Nonlinear Problems (NLP)
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Theoretical Study on A Neural Method for Combinatorial Optimization Problems
Sub Title (in English)
Keyword(1) Chaotic Neural Network
Keyword(2) Quadratic Assignment Problems
Keyword(3) Observation Function
1st Author's Name Keiichi SATO
1st Author's Affiliation Graduate School of Science and Engineering, Saitama University()
2nd Author's Name Tohru IKEGUCHI
2nd Author's Affiliation Graduate School of Science and Engineering, Saitama University
Date 2003/6/16
Paper # NLP2003-16
Volume (vol) vol.103
Number (no) 136
Page pp.pp.-
#Pages 6
Date of Issue