title: A parallel improvement algorithm for the bipartite subgraph problem.
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.
authors.affiliation: Cirrus Logic Inc., Fremont, CA.
authors.forename: K C
authors.initials: KC
authors.lastname: Lee
authors.forename: N
authors.initials: N
authors.lastname: Funabiki
authors.forename: Y
authors.initials: Y
authors.lastname: Takefuji