Abstract
The problem of finding the shortest tree connecting a set of points is called the Steiner minimal tree problem and is nearly three centuries old. It has applications in transportation, computer networks, agriculture, telephony, building layout and very large scale integrated circuit (VLSI) design, among others, and is known to be NP-complete. We propose a neural network which self-organizes to find a minimal tree. Solutions found by the network compare favourably with the best known or optimal results on test problems from the literature. To the best of our knowledge, the proposed network is the first neural-based solution to the problem. We show that the neural network has a built-in mechanism to escape local minima.
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Jayadeva, Bhaumik, B. A neural network for the Steiner minimal tree problem. Biol. Cybern. 70, 485–494 (1994). https://doi.org/10.1007/BF00203241
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DOI: https://doi.org/10.1007/BF00203241