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 |
Fingerprint
ASJC Scopus subject areas
- Software
Cite this
Pornavalai, C., Chakraborty, G., & Shiratori, N. (1995). Neural networks for solving Constrained Steiner Tree problem. In IEEE International Conference on Neural Networks - Conference Proceedings (Vol. 4, pp. 1867-1870). IEEE.