Learning Heuristics for OBDD Minimization by Evolutionary Algorithms
نویسندگان
چکیده
Ordered Binary Decision Diagrams (OBDDs) are the state-of-the-art data structure in CAD for ICs. OBDDs are very sensitive to the chosen variable ordering, i.e. the size may vary from linear to exponential. In this paper we present an Evolutionary Algorithm (EA) that learns good heuristics for OBDD minimization starting from a given set of basic operations. The diierence to other previous approaches to OBDD minimization is that the EA does not solve the problem directly. Rather, it developes strategies for solving the problem. To demonstrate the eeciency of our approach experimental results are given. The newly developed heuristics are more eecient than other previously presented methods.
منابع مشابه
Learning Heuristics for Obdd Minimization by Evolutionary Algorithms Learning Heuristics for Obdd Minimization by Evolutionary Algorithms
Ordered Binary Decision Diagrams (OBDDs) are the state-of-the-art data structure in CAD for ICs. OBDDs are very sensitive to the chosen variable ordering, i.e. the size may vary from linear to exponential. In this paper we present an Evolutionary Algorithm (EA) that learns good heuristics for OBDD minimization starting from a given set of basic operations. The diierence to other previous approa...
متن کاملA New Evolutionary Algorithm based BDD Optimization for Area and Power
Reduced Ordered Binary Decision Diagram (ROBDD) is the most popular data structure for efficient representation and manipulation of Boolean functions. However, this novel data structure is very sensitive to the variable ordering, i.e. the size may vary from linear to exponential. Since finding the optimal variable ordering is an NP-complete problem and the best known algorithm has exponential r...
متن کاملLearning heuristics for OKFDD minimization by evolutionary algorithms
| Ordered Kronecker Functional Decision Diagrams (OKFDDs) are a data structure for e cient representation and manipulation of Boolean functions. OKFDDs are very sensitive to the chosen variable ordering and the decomposition type list, i.e. the size may vary from linear to exponential. In this paper we present an Evolutionary Algorithm (EA) that learns good heuristics for OKFDD minimization sta...
متن کاملOPTIMAL CONSTRAINED DESIGN OF STEEL STRUCTURES BY DIFFERENTIAL EVOLUTIONARY ALGORITHMS
Structural optimization, when approached by conventional (gradient based) minimization algorithms presents several difficulties, mainly related to computational aspects for the huge number of nonlinear analyses required, that regard both Objective Functions (OFs) and Constraints. Moreover, from the early '80s to today's, Evolutionary Algorithms have been successfully developed and applied as a ...
متن کامل