Solving the Shortest Path Routing Problem Using Noisy Hopfield Neural Networks

To improve neural network algorithms for the shortest path routing problem (SPRP), we propose a solution using a noisy Hopfield neural network (NHNN), i.e., by adding decaying stochastic noise to the continuous Hopfield neural network (HNN). We also modify the energy function for the SPRP. Simulation results show that our approach achieves better route optimality compared to other algorithms that employ the HNN.