Synthesis of highly testable fixed-polarity AND-XOR canonical networks-A genetic algorithm-based approach

Specific inherent advantages of AND-XOR networks have encouraged researchers to look for efficient minimization and synthesis tools for their realization. Among several canonical representations of AND-XOR networks, the most easily testable one is the fixed polarity Consistent Generalized Reed Muller (CGRM) form. In this paper, a Genetic Algorithm (GA) formulation of the problem of finding the polarity of the variables resulting in minimum number of product terms has been proposed. The quality of the solution obtained and the high rate of convergence have established the effectiveness of the genetic algorithm in solving this particular NP-hard problem. Further, the inherent parallelism of genetic algorithm makes the proposed scheme an ideal candidate for solving the problem in a multiprocessor environment.