### Abstract

Hopfield neural network model for finding an optimal or shortest path between two nodes in a graph was proposed recently in some literatures. In this paper, we present a modified version of Hopfield model to find an optimal tree (least total cost tree) from a source node to a number of destination nodes, where each path from source to a destination must satisfy a constraint condition (delay bound condition). This problem is called Constrained Steiner Tree (CST) problem, and was proved to he a NP-complete. A new adaptive coefficient control method for the proposed Hopfield energy function is also developed. Through computer simulation, it is shown that the proposed model could always find a near-optimal valid solution.

Original language | English |
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Title of host publication | IEEE International Conference on Neural Networks - Conference Proceedings |

Place of Publication | Piscataway, NJ, United States |

Publisher | IEEE |

Pages | 1867-1870 |

Number of pages | 4 |

Volume | 4 |

Publication status | Published - 1995 |

Event | Proceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6) - Perth, Aust Duration: 1995 Nov 27 → 1995 Dec 1 |

### Other

Other | Proceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6) |
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City | Perth, Aust |

Period | 95/11/27 → 95/12/1 |

### Fingerprint

### ASJC Scopus subject areas

- Software

### Cite this

*IEEE International Conference on Neural Networks - Conference Proceedings*(Vol. 4, pp. 1867-1870). Piscataway, NJ, United States: IEEE.

**Neural networks for solving Constrained Steiner Tree problem.** / Pornavalai, Chotipat; Chakraborty, Goutam; Shiratori, Norio.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*IEEE International Conference on Neural Networks - Conference Proceedings.*vol. 4, IEEE, Piscataway, NJ, United States, pp. 1867-1870, Proceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6), Perth, Aust, 95/11/27.

}

TY - GEN

T1 - Neural networks for solving Constrained Steiner Tree problem

AU - Pornavalai, Chotipat

AU - Chakraborty, Goutam

AU - Shiratori, Norio

PY - 1995

Y1 - 1995

N2 - Hopfield neural network model for finding an optimal or shortest path between two nodes in a graph was proposed recently in some literatures. In this paper, we present a modified version of Hopfield model to find an optimal tree (least total cost tree) from a source node to a number of destination nodes, where each path from source to a destination must satisfy a constraint condition (delay bound condition). This problem is called Constrained Steiner Tree (CST) problem, and was proved to he a NP-complete. A new adaptive coefficient control method for the proposed Hopfield energy function is also developed. Through computer simulation, it is shown that the proposed model could always find a near-optimal valid solution.

AB - Hopfield neural network model for finding an optimal or shortest path between two nodes in a graph was proposed recently in some literatures. In this paper, we present a modified version of Hopfield model to find an optimal tree (least total cost tree) from a source node to a number of destination nodes, where each path from source to a destination must satisfy a constraint condition (delay bound condition). This problem is called Constrained Steiner Tree (CST) problem, and was proved to he a NP-complete. A new adaptive coefficient control method for the proposed Hopfield energy function is also developed. Through computer simulation, it is shown that the proposed model could always find a near-optimal valid solution.

UR - http://www.scopus.com/inward/record.url?scp=0029544664&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0029544664&partnerID=8YFLogxK

M3 - Conference contribution

VL - 4

SP - 1867

EP - 1870

BT - IEEE International Conference on Neural Networks - Conference Proceedings

PB - IEEE

CY - Piscataway, NJ, United States

ER -