Resource-constrained Project Scheduling (RCPS) is one of the NP-hard classes because of the complexity of their combinatorial nature. Any exact algorithms are difficult to handle such a problem. In addition, uncertainty also often exists in many projects in the process of the estimate of activity durations. This paper presents the framework of a fuzzy genetic algorithm combined with tabu mechanism for fuzzy RCPS in order to obtain an approximate optimal solution. This approach can handle both fuzzy and crisp numbers that commonly coexist in many realistic RCPS problems. To demonstrate the algorithm developed, a real case of an overhaul schedule is considered as a fuzzy RCPS problem.