Abstract
A novel combination of genetic algorithms and constraint satisfaction modelling for the solution of two and multi-layer over-the-cell channel routing problems is presented. The two major objectives of the optimization task are to find an optimal assignment of nets to over-the-cell and within the channel tracks, and to minimize the channel widths through a simple but effective iterative routing methodology. Two genetic algorithms cooperate in a nested manner to perform the optimization task. The results obtained using the benchmark problems published in literature indicate that, without any predefined fixed upper/lower channel widths, the implemented algorithm outperforms well-known channel routers.
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Acan, A., Unveren, A. (2004). An Evolutionary Constraint Satisfaction Solution for Over the Cell Channel Routing. In: Deb, K. (eds) Genetic and Evolutionary Computation – GECCO 2004. GECCO 2004. Lecture Notes in Computer Science, vol 3103. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24855-2_98
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DOI: https://doi.org/10.1007/978-3-540-24855-2_98
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