Using a Neural Network with Nonlinear Self-feedback to Solve the Maximum Clique Problem
Liu Huai-yi, Xiaofan Yang, Liping Sun, Si Pei, Can Wang · Journal of Chongqing University. English Edition · 2007
As the MCP is NP-hard,an efficient approach to treating this problem is to design appropriate recurrent neural networks.We develop a new algorithm for the MCP,which can,to a certain extent,prevent the associated neural network from falling into local optimal points.The proposed algorithm incorporates nonlinear self-feedback into the SLDN algorithm and has distinguished dynamical characteristics.Simulation results show that the performance of proposed algorithm is statistically superior to the SLDN algorithm.