Nelson and Staum derived ranking-and-selection (R&S) procedures that employ control-variate (CV) estimators instead of sample means to obtain greater statistical efficiency. However, control-variate estimators require more computational effort than sample means, and effective controls must be identified. In this paper, we present a new CV screening procedure to avoid much of the computation cost along with a better paired CV model than that of Nelson and Staum. We also present a two-stage CV combined procedure that captures the ability to eliminate inferior systems in the first stage and the statistical efficiency of control variates for selection in the second stage. Some guidelines about control-variate selection and an empirical evaluation are provided.