In this paper, we propose an analytic approach to the variable sifting based on weighting of qubits and gates. The proposed scheme allows us to optimally sift gates (multi-control single-target reversible gates) within a linear number of steps of computation and provides, in general, that a smaller number of SWAP gates are required to transform a reversible circuit into an Linear Nearest Neighbor (LNN) model than other competing approaches. The method is analyzed for two different models of implementations; it is verified on the experimental data and results are compared with the state-of-the-art algorithms for the design of LNN circuits.