The repetitive project is the project composed of several units with the same or similar operating contents such as the skyscraper building, the highway engineering, the MRT system, the high-speed railway, the airport runway and the pipe culvert engineering. For the repetitive project, one of the most important issues is to maintain work continuity. The purpose of work continuity is to reduce the idle time among units for the working team, which can efficiently reduce the idle cost and to enhance production efficiency. However, if any unexpected situation occurs, the reduction of idle time among units to meet the demand for the work continuity would cause that once the working team delay in the former unit, the beginning time of next unit will be crashed and then the total working period will be impeded. When the repetitive project is scheduled, one could efficiently utilize the float time of activities and maintain suitable work continuity; then the buffer time should be imposed among the units and the idle time of working should be reduced to lower the cost of project. The purpose of this research aims to study the impact from reducing the risk of uncertainty in the repetitive project, to apply the buffer time among the operation to dilute the dash of total working period from the unexpected incidents, as well as to consider the uncertain working period and cost and according to the situations of work continuity among each working team, to seek the optimal tradeoff between time and cost. Moreover, this study uses the Monte Carlo Simulation combined with the Optimization of Genetic Algorithms. Goal of decision is to optimize the total cost under the specific confidence level of a particular working duration. Finally, the analytic model of this research will be applied to conduct the practical case simulation, the best buffer time imposed among the units will be decided, and the results will be compared with the case findings from the documents.