Developing feasible loading patterns using perturbation theory methods

This work illustrates an approach to core reload design that combines the power of integer programming with the efficiency of generalized perturbation theory. The main use of the method is as a tool to help the design engineer identify feasible loading patterns with minimum time and effort. The technique is highly successful for the burnable poison (BP) loading problem, but the unpredictable behavior of the branch-and-bound algorithm degrades overall performance for large problems. Unfortunately, the combined fuel shuffling plus BP optimization problem falls into this latter classification. Overall, however, the method shows great promise for significantly reducing the manpower time required for the reload design process. And it may even give the further benefit of better designs and improved performance