Neural network for optimal steiner tree computation

Chotipat Pornavalai*, Norio Shiratori, Goutam Chakraborty

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    2 Citations (Scopus)


    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 languageEnglish
    Pages (from-to)139-149
    Number of pages11
    JournalNeural Processing Letters
    Issue number3
    Publication statusPublished - 1996


    • Hopfield model
    • Neural networks
    • Optimization
    • Steiner tree

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Neuroscience(all)


    Dive into the research topics of 'Neural network for optimal steiner tree computation'. Together they form a unique fingerprint.

    Cite this