Artificial neural network for minimum crossing number problem

The objective of the minimum crossing number problem is to embed the edges of a graph so that the total number of crossings is minimized. This 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.