A parallel improvement algorithm for the bipartite subgraph problem

@article{Lee1992API,
  title={A parallel improvement algorithm for the bipartite subgraph problem},
  author={Kuo Chun Lee and Nobuo Funabiki and Yoshiyasu Takefuji},
  journal={IEEE transactions on neural networks},
  year={1992},
  volume={3 1},
  pages={139-45}
}
The authors propose the first parallel improvement algorithm using the maximum neural network model for the bipartite subgraph problem. The goal of this NP-complete problem is to remove the minimum number of edges in a given graph such that the remaining graph is a bipartite graph. A large number of instances have been simulated to verify the proposed algorithm, with the simulation result showing that the algorithm finds a solution within 200 iteration steps and the solution quality is superior… CONTINUE READING

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