Neural network for optimal steiner tree computation

Chotipat Pornavalai; Norio Shiratori; Goutam Chakraborty

Neural network for optimal steiner tree computation

Chotipat Pornavalai, Norio Shiratori, Goutam Chakraborty

Research output: Contribution to journal › Article › peer-review

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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AU - Pornavalai, Chotipat

AU - Shiratori, Norio

AU - Chakraborty, Goutam

PY - 1996

Y1 - 1996

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AB - 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.

KW - Hopfield model

KW - Neural networks

KW - Optimization

KW - Steiner tree

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Neural network for optimal steiner tree computation

Abstract

Keywords

ASJC Scopus subject areas

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