Abstract: The reloading optimization problem of PWR with burnable absorber fuel is very difficult, and common optimization algorithms are inefficient and have bad global performance for it. Characteristic statistic algorithm (CSA) is very fit for the problem. In the past, the reloading optimization using CSA has shortcomings of separating the fuel assemblies’ loading pattern (LP) optimization from burnable absorber’s placement (BP) optimization. In this study, LP and BP were optimized simultaneously using CSA coupled with CYCLE2D, which is a core analysis code. The corresponding reloading coupling optimization software, CSALPBP, was developed. The 10th cycle reloading design of Daya Bay Nuclear Power Plant was optimized using CSALPBP. The results show that CSALPBP has high efficiency and excellent global performance.