New Hybrid Optimization Method and Its
Application to Pressurized Water Reactors Reloading Optimization
Wang Tao, Xie Zhongsheng
(School of Energy and Power Engineering, Xi'an Jiaotong University, Xi'an 710049, China)
Abstract: A new hybrid optimization method (GATB) is proposed, which combines the
genetic algorithm (GA) with the tabu search (TABU) . The hybrid method adopts global
search advantage of the GA and local search advantage of the TABU, and it possesses
improved ability and convergence speed. The proposed hybrid method was implemented to the
reactor reloading optimization calculation of WWER¡M1000 type reactor and Qinshan¡MI
nuclear power plant core reloading. For verifying the advantages of this method, The
reloading optimization calculations were performed by GATB and GA respectively using same
fitness function and control parameters. The numerical results show that the hybrid
optimization method converges faster and obtains better solution than GA.
Keywords: genetic algorithm; tabu search algorithm; hybrid optimization method; hexagonal