Enhancing Quine-McCluskey

Currently, the only algorithm that yields an exact solution to the boolean minimization problem is the well-known Quine-McCluskey, but almost all software solutions employ different implementations because of its two fundamental weaknesses: it is memory hungry and slow for a large number of causal conditions. This paper proposes an alternative to the classical Quine-McCluskey algorithm, one that addresses both problems, and especially the one of memory consumption. The solutions of this new algorithm are also exact, but they are produced not by following the cumbersome classical algorithm but using a more direct and faster approach. Memory restrictions limit the number of input variables (causal conditions) at a ceiling of about 14 or 15 (because each new variable expands the memory usage in a geometric proportion), where this alternative uses only a very small fraction of memory and it can process about 20 input variables with acceptable speed.