A method to improve multiobjective genetic algorithm optimization of a self-fuel-providing LMFBR by niche induction among nondominated solutions

A method to improve the optimization performance of a genetic algorithm (GA) for multiobjective optimization problems is proposed. It is based on niche induction among nondominated solutions that is ful®lled by the control on their reproduction potential by using a sharing function. It is applied to an equilibrium cycle fuel reloading pattern for a Self- Fuel-Providing Reactor, and it provides better results compared to ones obtained with an adaptation of a conventional method.