Reversible logic synthesis through ant colony optimization

We propose a novel synthesis technique for reversible logic based on ant colony optimization (ACO). In our ACO-based approach, reversible logic synthesis is formulated as a best-path search problem, where artificial ants, starting from their nest (reversible function output), attempt to find the best path to the food source (reversible function input). The experimental results have demonstrated superior performance in terms of both synthesis quality and computation time. They also show that the proposed method is scalable in handling large reversible functions.