A Study of Minimum s-t Cut Algorithm Using Maximum-Flow Neural Network on Directed / Undirected Graphs
Maximum-Flow Neural Network を用いた有向/ 無向グラフに対する最小s-t カットアルゴリズムの一検討

Masatoshi Sato, Hisashi Aomori, Mamoru Tanaka
2014 Journal of Signal Processing  
The maximum-flow neural network(MF-NN) is a novel neural network model for the maximum flow problem. From the max-flow min-cut theorem, it is known that the maximum flow problem and the minimum cut problem are dual problems. This indicates that MF-NN is applicable to the minimum cut algorithm. In this paper, we propose a novel minimum cut solution using MF-NN in directed and undirected graphs. Furthermore, since the proposed method is intended to circuit implementation based on nonlinear
more » ... theory, it has considerable potential for speeding up computation time. Keywords: maximum-flow neural network, nonlinear resistive circuit analysis, minimum cut maximum adjacency ordering method [6] 1956
doi:10.2299/jsp.18.259 fatcat:fjgk7q732nhzfgqzyr7jlzxwpu