Abstract: The design of burnable poisons (BPs) can compensate for excess reactivity at the beginning of lifetime of nuclear reactors and flatten power distribution, which is especially important for nuclear reactors assembly design. At present, the traditional optimization design mainly relies on the subjective experience and judgment of designers, which is complicated and timeconsuming. Therefore, the efficiency and reliability of BPs design urgently need to be improved. In this paper, the multiobjective parallel genetic algorithm (GA) was applied to the selection and optimization of the components of pressurized water reactor (PWR). Taking the reactivity control, power distribution and poisons residues in different periods as the objectives, the decision variables such as the type of BPs materials, the layout of fuel rods containing BPs materials, the purity of BPs and the axial division were optimized. Then optimization program was developed by combining multiobjective parallel GA with Monte Carlo particle transport code RMC as the neutronics and depletion solver. 13 and 40 optimization schemes were selected for two and threedimensional burnup calculation. The results show that the comprehensive effect of Er2O3 as BP is the best. The application of Gd2O3, Eu2O3 and Sm2O3 should be further studied in combination with the core scheme. HfO2 and Dy2O3 are not suitable for using as BPs. The results are basically consistent with the results obtained by manual search optimization. At the same time, threedimensional axial division can provide more alternative material types for optimization, and power peaking factor can be reduced by layering some BPs. This paper provides useful methods and tools for BPs design of nuclear reactors.