The increasing popularity of SAT and BDD techniques in formal hardware verification and automated synthesis of logic circuits encourages the search for additional speed-ups. Since typical SAT and BDD algorithms are exponential in the worst-case, the structure of real-world instances is a natural source of improvements. While SAT and BDD techniques are often presented as mutually exclusive alter...

We present a new approach to learning the structure and parameters of a Bayesian network based on regularized estimation in an exponential family representation. Here we show that, given a fixed variable order, the optimal structure and parameters can be learned efficiently, even without restricting the size of the parent variable sets. We then consider the problem of optimizing the variable or...

We present Value Elimination, a new algorithm for Bayesian Inference. Given the same variable ordering information, Value Elimination can achieve performance that is within a constant factor of variable elimination or recursive conditioning, and on some problems it can perform exponentially better, irrespective of the variable ordering used by these algorithms. Value Elimination’s other feature...

Abstract The size of Ordered Binary Decision Diagrams (OBDDs) is determined by the chosen variable ordering. A poor choice may cause an OBDD to be too large to fit into the available memory. The decision variant of the variable ordering problem is known to be NP -complete. We strengthen this result by showing that for each constant c > 1 there is no polynomial time approximation algorithm with ...

Ordered binary decision diagrams (OBDDs) have already proved useful for example in the veriication of combinational and sequential circuits. But the applications are limited, since the decriptive power of OBDDs is limited. Therefore several more general BDD models are studied. In this paper the so{called Parity{OBDDs are considered. The two polynomial time algorithms given are motivated by the ...

Generally ordering policies are done by two methods, including fix order quantity (FOQ) and fix order period (FOP). These methods are static and either the quantity of ordering or the procedure of ordering is fixing in throughout time horizon. In real environments, demand is varying in any period and may be considered as uncertainty. When demand is variable in any period, the traditional and st...

We develop two heuristics for reducing the time andspace required to obtain a binary decision diagram representation ofthe solutions of a configuration problem. First, we show that dynam-ics of the growth in the size of the decision diagram depend stronglyon the order in which constraints are added and propose a heuristicconstraint ordering algorithm that uses the distinctiv...