Abstract

A novel and efficient partitioning algorithm, called genetic partitioning, utilizing genetic algorithms is presented. Genetic partitioning has the capability of (1) climbing uphill with respect to the best solution and (2) implicit parallel processing due to population inherent in genetic algorithms. Two circuits are examined. The results of the first circuit are optimal in 85% of the cases when compared with those obtained using the exhaustive search approach. Genetic partitioning is competitive with simulated annealing in speed, as verified by the second circuit. >

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