Disjoint Sum of Product Minimization by Evolutionary Algorithms

Recently, an approach has been presented to minimize Disjoint Sum-of-Products (DSOPs) based on Binary Decision Diagrams (BDDs). Due to the symbolic representation of cubes for large problem instances, the method is orders of magnitude faster than previous enumerative techniques. But the quality of the approach largely depends on the variable ordering of the underlying BDD. This paper presents an Evolutionary Algorithm (EA) to optimize the DSOP representation of a given Boolean function. The EA is used to find an optimized variable ordering for the BDD representation. Then the DSOP is derived from the optimized BDD using structural and symbolic techniques. Experiments are performed to adjust the parameters of the EA. Experimental results are given to demonstrate the efficiency of the approach.