AbstractConstruction projects often face various uncertainties during their execution. Even if planned project schedules are optimal with respect to time or cost, their implementation may be affected by these uncertainties, resulting in project delays, cost overruns, or both. To address this challenge, this study presents a multiobjective robust optimization model for scheduling repetitive projects under the line-of-balance (LOB) framework, with the objective of minimizing the project cost while maximizing the schedule robustness without exceeding a given deadline. The ability of an LOB schedule to protect against unexpected events caused by various uncertainties was quantified using a new robustness measure. The proposed model was then extended to consider the constraints of available cash with the objective of devising financially feasible and stable schedules. The practicability of the proposed robust optimization model and the effectiveness of the robustness measure were verified by a highway project. The results show that the model can construct the optimal trade-off curve between project cost and schedule robustness, of which the most suitable schedule can be determined once additional information about the level of uncertainty and its impact are provided.