Abstract
Hopfield neural network model for finding the 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 a more general problem of searching an optimal tree (least total cost tree) from a source node to a number of destination nodes in a graph. This problem is called Steiner tree in graph theory, where it is proved to be a NP-complete. Through computer simulations, it is shown that the proposed model could always find an optimal or near-optimal valid solution in various graphs.
| Original language | English |
|---|---|
| Pages (from-to) | 139-149 |
| Number of pages | 11 |
| Journal | Neural Processing Letters |
| Volume | 3 |
| Issue number | 3 |
| Publication status | Published - 1996 |
Keywords
- Hopfield model
- Neural networks
- Optimization
- Steiner tree
ASJC Scopus subject areas
- Artificial Intelligence
- Neuroscience(all)
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Cite this
Pornavalai, C., Shiratori, N., & Chakraborty, G. (1996). Neural network for optimal steiner tree computation. Neural Processing Letters, 3(3), 139-149.