NEW ASPECTS IN OPTIMIZATION OF BDDS: MIXED TECHNIQUES BASED ON POPULATIONS OF SOLUTIONS AND LOWER BOUND
IULIAN FURDU 1, PETRU GABRIEL PUIU 2 1. “Vasile Alecsandri" University of Bacău, Faculty of Sciences, Department of Mathe-matics, Informatics and Educational Sciences, Calea Mărăşeşti 157, Bacău 600115, Ro-mania, e-mail: ifurdu@ub.ro
2. “Vasile Alecsandri” University of Bacău, Faculty of Engineering, Department of Power Engineering, Mechatronics and Computer Science, 157 Calea Mărăşeşti, Bacău, 600115, Romania, e-mail: ppgabriel@ub.ro
This paper provides a comprehensive introduction on recent advances to reduced ordered binary decision diagrams (ROBDDs or BDDs) as a state-of-the-art data structure in computed-aided design. Key aspects concerning the use of techniques based on lower bounds in the context of BDD optimization are investigated. Three embryonic genetic algorithms for BDD optimization are presented (from which a new one) and their performance compared.
