Arc and path consistence revisited
Artificial Intelligence
Integer programming vs. expert systems: an experimental comparison
Communications of the ACM
A multi-layer channel router with new style of over-the-cell routing
DAC '92 Proceedings of the 29th ACM/IEEE Design Automation Conference
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
A Genetic Algorithm for Channel Routing Problem
Proceedings of the 5th International Conference on Genetic Algorithms
DAC '76 Proceedings of the 13th Design Automation Conference
An efficient approach to multilayer layer assignment with an application to via minimization
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Via design rule consideration in multilayer maze routing algorithms
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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A novel evolutionary assignment-ordering approach for combinatorial optimization using constraint satisfaction problem (CSP) modeling is presented. In the assignment of values to variables, the order of assignment is determined by an ordering function combined with problem-specific features. No a priori information is available on the assignment-ordering function and it is completely determined by evolutionary optimization to produce the best assignment results. Indeed, experimental evaluations show that the proposed method outperforms very well-known approaches for the solution of NP-hard combinatorial optimization problems from VLSI layout design, namely, channel routing and multi-layer over the cell channel routing.