Solving the minimum crossing number problem using an improved artificial neural network

Abstract

The minimum crossing number problem has important applications in printed circuit board layout, VLSI circuit routing, and automated graph drawing. In this paper, we propose an improved Hopfield neural network algorithm for efficiently solving the minimum crossing number problem. To evaluate the proposed algorithm, a large number of instances have been simulated. The simulation results show that the proposed algorithm is much better than previous works for solving the minimum crossing number problem in terms of the computation time and the solution quality. © Springer-Verlag Berlin Heidelberg 2006.