An Improved Algorithm for Network Reliability Evaluation

Binary Decision Diagram (BDD) is a data structure proved to be compact in representation and efficient in manipulation of Boolean formulas. Using Binary decision diagram in network reliability analysis has already been investigated by some researchers. In this paper we show how an exact algorithm for network reliability can be improved and implemented efficiently by using CUDD - Colorado University Decision Diagram

Efficient OBDD-based Boolean manipulation in CAD beyond current limits

We present the concept of TBDD's which considerably enlarges the class of Boolean functions that can be efficiently manipulated in terms of small size OBDD's. This is done by applying the concept of domain transformations, which is well-known in many areas of mathematics, physics, and technical sciences, to the context of BDD-based Boolean function manipulation in CAD: instead of working with the OBDD-representation of a function f, TBDD's allow to work with an OBDD-representation of a suited cube transformed version of f. Besides of giving some theoretical insights into the new concept, we investigate in some detail cube transformations which are based on complete types. We show that such TBDD-representations can be derived similarly as OBDD-representations, give evidence of the practical importance of such TBDD's by presenting very small-size TBDD-representations of the hidden weighted bit functions HWB_n which were proved to have only large OBDD-representations, and report some promising experimental results with the ISCAS benchmark multiplier circuit C6288. (orig.)Available from TIB Hannover: RR 1843(94-16) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman

Efficient OBDD-Based Boolean Manipulation in CAD Beyond Current Limits

We present the concept of TBDD's which considerably enlarges the class of Boolean functions that can be efficiently manipulated in terms of OBDD's. It extends the idea of using domain transformations, which is well-known in many areas of mathematics, physics, and technical sciences, to the context of OBDD--based Boolean function manipulation in CAD: Instead of working with the OBDDrepresentation of a function f , TBDD's allow working with an OBDD-representation of a suited cube transformed version of f . Besides of giving some theoretical insights into the new concept, we investigate in some detail cube transformations which are based on complete types. We ffl show that such TBDD--representations can be derived similarly as OBDD--representations, ffl give evidence of the practical importance of such TBDD's by presenting very small-size TBDDrepresentations of the hidden weighted bit functions HWBn which were proved to have only very large OBDD-representations, and ffl report some pr..

Artificial evolution with Binary Decision Diagrams: a study in evolvability in neutral spaces

This thesis develops a new approach to evolving Binary Decision Diagrams, and uses it to study evolvability issues. For reasons that are not yet fully understood, current approaches to artificial evolution fail to exhibit the evolvability so readily exhibited in nature. To be able to apply evolvability to artificial evolution the field must first understand and characterise it; this will then lead to systems which are much more capable than they are currently. An experimental approach is taken. Carefully crafted, controlled experiments elucidate the mechanisms and properties that facilitate evolvability, focusing on the roles and interplay between neutrality, modularity, gradualism, robustness and diversity. Evolvability is found to emerge under gradual evolution as a biased distribution of functionality within the genotype-phenotype map, which serves to direct phenotypic variation. Neutrality facilitates fitness-conserving exploration, completely alleviating local optima. Population diversity, in conjunction with neutrality, is shown to facilitate the evolution of evolvability. The search is robust, scalable, and insensitive to the absence of initial diversity. The thesis concludes that gradual evolution in a search space that is free of local optima by way of neutrality can be a viable alternative to problematic evolution on multi-modal landscapes