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 |
|---|---|
| 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) |
|---|---|
| City | Perth, Aust |
| Period | 95/11/27 → 95/12/1 |
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ASJC Scopus subject areas
- Software
Cite this
Neural networks for solving Constrained Steiner Tree problem. / Pornavalai, Chotipat; Chakraborty, Goutam; Shiratori, Norio.
IEEE International Conference on Neural Networks - Conference Proceedings. Vol. 4 Piscataway, NJ, United States : IEEE, 1995. p. 1867-1870.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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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
AN - SCOPUS:0029544664
VL - 4
SP - 1867
EP - 1870
BT - IEEE International Conference on Neural Networks - Conference Proceedings
PB - IEEE
CY - Piscataway, NJ, United States
ER -