An efficient variable ordering strategy for ordered binary decision diagrams (OBDD) based on interleaving the compacted clusters is proposed in this paper. The novelty of this method is to apply the divide-and-conquer approach to find a good variable ordering efficiently for circuits with a large number of I/ Os. First, a given circuit is partitioned into a number of clusters according to the c...

Decision Diagrams (DDs) are a data structure for the representation and manipulation of discrete logic functions often applied in VLSI CAD. Common DDs to represent Boolean functions are Binary Decision Diagrams (BDDs). Multiple-valued logic functions can be represented by Multiple-valued Decision Diagrams (MDDs). The efficiency of a DD representation strongly depends on the variable ordering; t...

Regularization of covariance matrices in high dimensions is usually either based on a known ordering of variables or ignores the ordering entirely. This paper proposes a method for discovering meaningful orderings of variables based on their correlations using the Isomap, a non-linear dimension reduction technique designed for manifold embeddings. These orderings are then used to construct a sp...

In this paper we present an Evolutionary Algorithm (EA) that learns good heuristics from a given set of basic operations, i.e. local search search algorithms. The heuristics are given by sequences of these operations. The length of a sequencea depends on the considered problem instance, i.e. on the number of basic operations that have to be used for constructing an eecient heuristic. The sequen...

In Variable Neighborhood Descent (VND) it is often difficult to decide upon the ordering in which a different types of neighborhoods are considered. This arrangement typically strongly affects the quality of finally obtained solution as well as computation time. We present a VND variant which orders the neighborhoods dynamically in a self-adaptive way during the optimization process. Each neigh...

The Binary Decision Diagram (BDD) based compilation schemes are quite suitable for representing configuration knowledge bases. It is well-known that the size of BDDs are very sensitive to the variable order. In this paper, we study the variable ordering problem of BDDs when they represent a configuration knowledge. Such a study is crucial to better understand the BDD-based compilation schemes. ...

We consider the impact of value ordering heuristics on the search effort required to find all solutions, or proving none exist, to a constraint satisfaction problem in k-way branching search. We show that when the variable ordering heuristic is adaptive, the order in which the values are assigned to variables can make a significant difference in all measures of search effort. We study in depth ...

We present Value Elimination, a new algorithm for Bayesian Inference. Given the same variable order­ ing information, Value Elimination can achieve per­ formance that is within a constant factor of variable elimination or recursive conditioning, and on some problems it can perform exponentially better, irrespec­ tive of the variable ordering used by these algorithms. Value Elimination's other f...