A parallel improvement algorithm for the bipartite subgraph problem |
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Authors: | Lee KC Funabiki N Takefuji Y |
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Affiliation: | Cirrus Logic Inc., Fremont, CA. |
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Abstract: | 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 to that of the best existing algorithm. The algorithm is extended for the K-partite subgraph problem where no algorithm has been proposed. |
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