Abstract
An efficient parallel algorithm for solving the minimum vertex cover problem using binary neural network is presented. The proposed algorithm which is designed to find the smallest vertex cover of a graph, uses the binary neural network to get a near-smallest vertex cover of the graph, and adjusts the balance between the constraint term and the cost term of the energy function to help the network escape from the state of the near-smallest vertex cover to the state of the smallest vertex cover or better one. The proposed algorithm is tested on a large number of random graphs and benchmark graphs. The simulation results show that the proposed algorithm is very satisfactory and better than previous works for solving the minimum vertex cover problem.
