Abstract
A novel neural network approach using the maximum neuron model is presented for N-queens problems. The goal of the N-queens problem is to find a set of locations of N queens on an N × N chessboard such that no pair of queens commands each other. The maximum rjeuron model proposed by Takefuji et al. has been applied to two optimization problems where the optimization of objective functions is requested without constraints. This paper demonstrates the effectiveness of the maximum neuron model for constraint satisfaction problems through the N-queens problem. The performance is verified through simulations in up to 500-queens problems on the sequential mode, the N-parallel mode, and the N2-parallel mode, where our maximum neural network shows the far better performance than the existing neural networks.
| Original language | English |
|---|---|
| Pages (from-to) | 251-255 |
| Number of pages | 5 |
| Journal | Biological Cybernetics |
| Volume | 76 |
| Issue number | 4 |
| Publication status | Published - 1997 |
| Externally published | Yes |
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ASJC Scopus subject areas
- Biophysics
Cite this
A maximum neural network approach for N-queens problems. / Funabiki, Nobuo; Takenaka, Yoichi; Nishikawa, Seishi.
In: Biological Cybernetics, Vol. 76, No. 4, 1997, p. 251-255.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - A maximum neural network approach for N-queens problems
AU - Funabiki, Nobuo
AU - Takenaka, Yoichi
AU - Nishikawa, Seishi
PY - 1997
Y1 - 1997
N2 - A novel neural network approach using the maximum neuron model is presented for N-queens problems. The goal of the N-queens problem is to find a set of locations of N queens on an N × N chessboard such that no pair of queens commands each other. The maximum rjeuron model proposed by Takefuji et al. has been applied to two optimization problems where the optimization of objective functions is requested without constraints. This paper demonstrates the effectiveness of the maximum neuron model for constraint satisfaction problems through the N-queens problem. The performance is verified through simulations in up to 500-queens problems on the sequential mode, the N-parallel mode, and the N2-parallel mode, where our maximum neural network shows the far better performance than the existing neural networks.
AB - A novel neural network approach using the maximum neuron model is presented for N-queens problems. The goal of the N-queens problem is to find a set of locations of N queens on an N × N chessboard such that no pair of queens commands each other. The maximum rjeuron model proposed by Takefuji et al. has been applied to two optimization problems where the optimization of objective functions is requested without constraints. This paper demonstrates the effectiveness of the maximum neuron model for constraint satisfaction problems through the N-queens problem. The performance is verified through simulations in up to 500-queens problems on the sequential mode, the N-parallel mode, and the N2-parallel mode, where our maximum neural network shows the far better performance than the existing neural networks.
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UR - http://www.scopus.com/inward/citedby.url?scp=0000055318&partnerID=8YFLogxK
M3 - Article
VL - 76
SP - 251
EP - 255
JO - Biological Cybernetics
JF - Biological Cybernetics
SN - 0340-1200
IS - 4
ER -