Global manufacturing can be viewed as a project-oriented environment, where an effective project baseline schedule can serve as basis for planning external activities, such as material procurement, preventive maintenance and commitment to shipping dates to customers. However, real life project scheduling often encounters imprecise activity durations and resource-constraints. The fuzzy set theory provides natural modeling tools for dealing with imprecise activity durations. In this paper, based on the fuzzy set theory, a specific genetic local search (GLS) algorithm is designed to solve fuzzy resource-constrained project scheduling problems. A precedence feasible activity list is applied as a solution representation, and specially designed recombination operators and local search processes are used in our algorithm. The roulette wheel section and the elite retaining model are incorporated to generate a new population for the next generation. A practical project schedule with different resource availability levels is used in computational experiments computational results show that the GLS algorithm is effective for solving this kind of problem.