An application of genetic multi-objective optimization algorithm to neutron spectrum unfolding problem

Since it is difficult to directly measure neutron energy, the neutron spectrum is estimated from the specific responses of the neutron reaction. Although several algorithms have been proposed to reconstruct the neutron spectrum, no attempt has been made to apply a multi objective optimization technique. This study is based on the idea that reconstructing the spectrum by taking into consideration various prior information simultaneously enables to obtain more reasonable results. The genetic multi-objective optimization scheme was applied to derive the Pareto front of spectrum from activation foil responses. The two objectives of maximizing the Shannon information entropy of the neutron spectrum and minimizing the relative error of the responses were considered. By applying the algorithm, we were able to successfully reduce the solution candidates to Pareto front and improve the validity of the unfolded spectrum.