Algorithm for solving bipartite subgraph problem with probabilistic self-organizing learning

Self-organizing model has been successfully applied to solving some combinatorial optimization problems, including the travelling salesman problem, the routing problem and the cell-placement problem, but there has not much work reported on its application to solving the graph partitioning problem. We propose a novel mapping which has not been proposed before, with some changes to the original Kohonen´s (1982) algorithm so as to enable it to solve a partitioning problem-the bipartite subgraph problem. This new approach is compared with to the maximum neural network for solving the same problem, showing that the performance of our new approach is superior to that of the maximum neural network