Title :
Improved variable ordering of BDDs with novel genetic algorithm
Author :
Zhuang, N. ; Benten, M.S.T. ; Cheung, P.Y.K.
Author_Institution :
Dept. of Electr. & Electron. Eng., Imperial Coll. of Sci., Technol. & Med., London, UK
Abstract :
A new algorithm for variable ordering of binary decision diagram (BDD) is presented. The algorithm is based on a novel formulation of the Genetic Algorithm (GA) employing three dynamic GA parameters: population size, mutation rate and stop criteria. Test results using LGSynth93 benchmark circuits show that the new algorithm offers considerable improvements on large circuits when compared with previously published results
Keywords :
Boolean functions; genetic algorithms; BDD; GSynth93 benchmark circuit; binary decision diagram; dynamic parameters; genetic algorithm; mutation rate; population size; stop criteria; variable ordering; Benchmark testing; Binary decision diagrams; Biological cells; Boolean functions; Circuit testing; Data structures; Educational institutions; Genetic algorithms; Genetic mutations; Very large scale integration;
Conference_Titel :
Circuits and Systems, 1996. ISCAS '96., Connecting the World., 1996 IEEE International Symposium on
Conference_Location :
Atlanta, GA
Print_ISBN :
0-7803-3073-0
DOI :
10.1109/ISCAS.1996.541621
