Title :
A new and efficient partitioning algorithm: genetic partitioning
Author :
Jin, Lin-Ming ; Chan, Shu-Park
Author_Institution :
Circuits & Syst. Res. Lab., Santa Clara Univ., CA, USA
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
Keywords :
genetic algorithms; parallel algorithms; genetic algorithms; genetic partitioning; hill climbing; implicit parallel processing; partitioning algorithm; Circuit simulation; Circuits and systems; Genetic algorithms; Genetic engineering; Genetic mutations; Laboratories; Parallel processing; Partitioning algorithms; Simulated annealing; Very large scale integration;
Conference_Titel :
Circuits and Systems, 1991., Proceedings of the 34th Midwest Symposium on
Conference_Location :
Monterey, CA
Print_ISBN :
0-7803-0620-1
DOI :
10.1109/MWSCAS.1991.252013