Abstract: There are many uncertain factors during the implementation of real-life projects. Robust scheduling is an effective method to deal with uncertainties and reduce schedule deviations of a project. In addition, the multi-skilled resources with uneven capacities widely exist in real projects, which may increase the difficulty of scheduling. However, such resources can also enlarge the optimization space for robust project scheduling due to the flexible substitution and cooperation relationships among them. Based on this, a two-stage algorithm is proposed to solve the multi-skilled project scheduling problem with uneven resource capacities (URC-MSPSP). In the first stage, a rule-based heuristic algorithm is designed through combining activity priority rules and resource weight rules. A 0-1 linear programming model is built for solving the baseline scheduling plan and resource allocation strategies. Then in the second stage, a robust optimization algorithm is designed for the baseline scheduling plan by biased random insertion and deletion of time buffering, as well as the adjustment of resource allocation strategies.. Simulation experiments show that the proposed algorithm is significantly superior to other algorithms in terms of robustness for projects with different scales under different risk levels.

Key words: multi-skilled resource, uneven capacity, project scheduling, robust optimization, scattered buffer