Variable Ordering of BDDs with Parallel Geneti

Variable Ordering of BDDs with Parallel Geneti Algorithms

On Threshold BDDs and the Optimal Variable Ordering Problem

Many combinatorial optimization problems can be formulated as 0/1 integer programs (0/1 IPs). The investigation of the structure of these problems raises the following tasks: count or enumerate the feasible solutions and find an optimal solution according to a given linear objective function. All these tasks can be accomplished using binary decision diagrams (BDDs), a very popular and effective...

Improving BDD Variable Ordering Using Abstract BDDs and Sampling

Variable ordering for BDDs has been extensively investigated. Recently, sampling based ordering techniques have been proposed to overcome problems with structure based static ordering methods and sifting based dynamic reordering techniques. However, existing sampling techniques can lead to an unacceptably large deviation in the size of the final BDD. In this paper, we propose a sampling techniq...

Integrating a Variable Ordering Heuristic with BDDs and CSP Decomposition Techniques for Interactive Configurators

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. ...

What's in It for My BDD? On Causal Graphs and Variable Orders in Planning

One decisive factor for the success of symbolic search using BDDs is whether or not the variable ordering is good. A general intuition is that smaller BDDs result if inter-dependent variables are close together. The most common means to capture variable dependencies in planning are causal graphs, and consequently previous work defined variable orders based on these. Starting from the observatio...