Projects are subject to various uncertainties that have negative effect on activity durations. This is most apparent in the case of construction projects. The actual completion time of construction projects is reported to be rarely in accordance with initial plans. A schedule considered optimal with respect to project duration may become infeasible due to disruptions caused by uncontrollable factors. Deficiencies of the existing methods of project scheduling gave rise to the worldwide search for predictive (or proactive) scheduling that is expected to provide robust schedules (immune to disturbances), thus counteracting instability and “nervousness” of a project plan. The baseline schedule (execution plan prepared prior to the project execution) is to be reliable in terms of not only the total project makespan, but also timing of particular tasks and activities – related with resource management. The main reason for the planner’s insisting on stable baseline schedules is the necessity of “advance booking” of key staff or equipment (to guarantee their availability) and keeping fixed delivery dates (as required by suppliers or subcontractors). A stable schedule with acceptable makespan performance should minimize the instability cost function, defined as the weighted sum of the expected absolute deviations between the predicted start times and the value that the random variable of start time will assume during schedule execution. Computational burden of optimizing this direct measure of schedule robustness in a real-life project environment is quite high. Developing surrogate quantitative measures to provide a good estimate of schedule robustness is essential for building efficient robust scheduling algorithms. For this reasons, the aim of this paper is to evaluate the quality of free-slack-based measures for a benchmark project. The new approach to increasing schedule robustness, based on buffer sizing and allocation, is proposed and tested against the existing free-slack times relocation approaches.