Abstract: In this paper, genetic algorithms（GA） and tabu search（TS） algorithm are applied to optimize the burnable absorber fuel loading problem for nuclear power plant reactor. The tenth-cycle of Daya-Bay Nuclear Power Station is taken as the example, and three general kinds of burnable absorber, i.e., boron, Gd₂O₃ and IFBA, are optimized using GA separately. Calculation results demonstrate that GA is effective for optimizing the burnable absorber loading and the IFBA works the best for PWR. Finally a hybrid optimization method that combined with GA and TS is used. The initial optimized results of GA are taken as the initial point of TS searching. This method saves much calculation time.