A genetic approach for network partitioning

Abstract

A new partitioning algorithm, genetic partitioning, utilizing genetic algorithms is presented. The genetic partitioning has the abilities of climbing uphill with respect to the best solution, and of implicit parallel processing due to its 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 performance, as verified by the second circuit.