Pressurized water reactor reloading optimization using genetic algorithms

The application of genetic algorithms (GAs) to pressurized water reactor (PWR) reloading pattern optimization is described. Standard bit-based genetic operators are used to optimize the arrangement of assemblies, burnable absorber, and burnt assembly orientations. The developed system has a modular structure. The GAs operators, reactor physics code, constraint conditions and objective function are all flexible. Test examples illustrating the effectiveness and flexibility of this system are presented and optimization results are discussed.