The execution of industrial projects is subject to uncertainties that cause deviations from the designated project schedules. Therefore, it is desired to generate robust schedules in the sense of being insensitive to project disruptions, such as deviations in activity durations. Beyond that, efficient schedules that offer high robustness at a low cost are preferred. This paper focuses on the discrete time-cost tradeoff problem and develops a new method for identifying and ranking efficient schedules. First, a large schedule pool with robust schedules is generated. Efficient schedules are then identified and ranked by applying data envelopment analysis (DEA) with a particular super-efficiency model. An extensive evaluation based on a project testbed and an example construction project shows that the proposed method finds and ranks efficient schedules, that can be suitably presented to a project manager for decision support.