Genetic algorithm for variable ordering of OBDDs

A genetic algorithm (GA) is applied to find a variable ordering that minimises the size of ordered binary decision diagrams (OBDDs). OBDDs are a data structure for representation and manipulation of Boolean functions often applied in CAD. The choice of the variable ordering largely influences the size of the OBDD (i.e. its size may vary from polynomial to exponential in the number of variables). Dynamic variable ordering is the state-of-the-art method for finding good variable orderings. In the paper it is shown by experimental results that better sizes can be obtained using GAs. The authors´ GA approach is a practical alternative to the exact algorithm for variable ordering. It produced optimal results for most considered benchmarks, but it is also applicable to functions with more than 20 variables due to its short runtimes