Layer Assignment Problem for Three-Layer Routing
IEEE Transactions on Computers
Analog VLSI and neural systems
Analog VLSI and neural systems
Solutions to the module orientation and rotation problems by neural computation networks
DAC '89 Proceedings of the 26th ACM/IEEE Design Automation Conference
A neural network design for circuit partitioning
DAC '89 Proceedings of the 26th ACM/IEEE Design Automation Conference
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
DAC '76 Proceedings of the 13th Design Automation Conference
DAC '82 Proceedings of the 19th Design Automation Conference
Efficient Algorithms for Channel Routing
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Dogleg Channel Routing is NP-Complete
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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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.