Neural networks for solving Constrained Steiner Tree problem

Chotipat Pornavalai*, Goutam Chakraborty, Norio Shiratori

*この研究の対応する著者

    研究成果: Conference contribution

    2 被引用数 (Scopus)

    抄録

    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.

    本文言語English
    ホスト出版物のタイトルIEEE International Conference on Neural Networks - Conference Proceedings
    Place of PublicationPiscataway, NJ, United States
    出版社IEEE
    ページ1867-1870
    ページ数4
    4
    出版ステータスPublished - 1995
    イベントProceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6) - Perth, Aust
    継続期間: 1995 11 271995 12 1

    Other

    OtherProceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6)
    CityPerth, Aust
    Period95/11/2795/12/1

    ASJC Scopus subject areas

    • ソフトウェア

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