Artificial Neural Network with Transient Chaos for Four-Coloring Map Problems and K-Colorability Problems
Xiuhong Wang · Systems Engineering - Theory & Practice · 2002
Neural network and computational energy are presented for solving four-coloring map problem. Then, the four-coloring map problems are solved by a neural network model with transient chaos (TCNN) which have higher ability of quickly searching for the globally optimal solution because of its complicated chaotic dynamics. Numerical simulations of four-coloring map problem show that TCNN would not be stuck into local minima like the conventional Hopfield neural network (HNN) and always guaranteed that computational energy converged to the globally optimal solution. The TCNN is extended for solving $K$-colorability problem which is one of NP-complete problems.