An Efficient Shortest Path Routing Algorithm Based on Improved Chaotic Neural Network

In this paper an efficient shortest path algorithm, which is an improved version of the transient chaotic neural network (TCNN), is presented. By eliminating the components of the eigenvectors with eminent negative eigenvalues of the weight matrix, this proposed method can avoid oscillation and offer a considerable acceleration of converging to the optimal solution when TCNN is used to search the optimal solution of shortest path problems. Numerical simulations of shortest path problem show that TCNN with modified weight matrix requires less iteration than TCNN with standard weight matrix before reaching optimal solution.