Optimization of MPRM functions using tabular techniques and genetic algorithms

This paper presents new techniques and algorithms to compute and optimize Mixed Polarity Reed Muller logic functions (MPRM) using Tabular techniques and Genetic Algorithms (GA). The first algorithm is used for bidirectional conversion between Fixed Polarity Reed Muller forms (FPRM) and MPRM and to derive any mixed polarity from another MPRM for any number of variables. The second algorithm is used to generate reduced MPRM expressions from FPRM for any number of variables based on tabular techniques. The last two algorithms are to find optimal MPRM among 3n different polarities using GA for large functions but without generating all the polarity sets for single and multi output sum-of-products (SOP) Boolean functions. All algorithms are implemented in C++ and fully tested using standard benchmark examples.