Reversible Logic Circuit Synthesis and Optimization Using Adaptive Genetic Algorithm

Abstract

In the recent years reversible logic circuits have gained a remarkable interest in the light of advancements made in quantum computation. The promise of theoretically zero power consumption is a major driving force for researchers to develop circuits using this logic. Synthesis of reversible logic and generating reversible logic circuit automatically with lower cost always has been a challenging task as reducing the search space is one of the major issues in the synthesis process using permutation. In this work, we proposed an Adaptive Genetic Algorithm (AGA) for synthesizing reversible logic circuits. NCT (NOT, CNOT, Toffoli) gate based library has been considered for synthesis of reversible logic circuits (RLC). The proposed algorithm produces a cascade of Toffoli gates for a given reversible specification of a circuit. Comparison of experimental results for several benchmark circuits shows that proposed evolutionary algorithm enables optimal or near-optimal solutions with lesser Gate Counts.