Loading pattern optimization of PWR reactors using Artificial Bee Colony

In this paper a core reloading technique using Artificial Bee Colony algorithm, ABC, is presented in the context of finding an optimal configuration of fuel assemblies. The proposed method can be used for in-core fuel management optimization problems in pressurized water reactors. To evaluate the proposed technique, the power flattening of a VVER-1000 core is considered as an objective function although other variables such as Keff, power peaking factor, burn up and cycle length can also be taken into account. The proposed optimization method is applied to a core design optimization problem previously solved with Genetic and Particle Swarm Intelligence Algorithm. The results, convergence rate and reliability of the new method are quite promising and show that the ABC algorithm performs very well and is comparable to the canonical Genetic Algorithm and Particle Swarm Intelligence, hence demonstrating its potential for other optimization applications in nuclear engineering field as, for instance, the cascade problems.

► ABC algorithm is comparable to the canonical GA algorithm and PSO.
► The performance of ABC shows that the algorithm is quiet promising.
► The final band width of search fitness values by ABC is narrow.
► The ABC algorithm is relatively easy to implement.