Optimization of fuel loading pattern for a material test reactor using swarm intelligence

A software design tool has been developed for optimization of in-core fuel loading pattern by using a biologically inspired computational search algorithms including Particle Swarm optimization. Catfish algorithm is also incorporated to protect the algorithm to be stuck during iteration process. An optimum core loading scheme has been proposed for a swimming pool type material test reactor (Pakistan Research Reactor-1) by maximizing the effective multiplication factor. This particle swarm optimization code and a diffusion theory code PRIDE has been integrated to search for an optimal loading pattern. Moreover as a second step, to maintain the integrity of fuel, a penalty function is also added to achieve a multi-objective optimization i.e. to maximize the effective multiplication factor while keeping the power peaking factor low.