AN APPLICATION OF NEURAL NETWORKS ON CHANNEL ROUTING PROBLEM

The channel routing problem is to make interconnections among terminals located on opposite sides of a rectangular channel. This problem has been proven to be NP-complete. Most of currently available algorithms are heuristic. This paper proposes a neural network based on the Hopfield and Tank model to handle the channel routing problem. Neural network has been successfully applied to many combinatorial optimization problems. However, applying this technique to channel routing problem has never been reported. Network configuration and operations of our design are thoroughly discussed in this paper. Typical examples from published literature are taken for experiments. The theoretical lower bounds are achieved in all examples.