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. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Chaotic Neural Network / Quadratic Assignment Problems / Observation Function |
Paper # | NLP2003-16 |
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Conference Information | |
Committee | NLP |
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Conference Date | 2003/6/16(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Nonlinear Problems (NLP) |
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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 |