A multi-objective evolutionary algorithm with a separate archive

In this paper a new algorithm has been developed for solving constrained non-linear multi-objective optimization problems. This algorithm was acquired by the modification of an earlier algorithm, while we use other selection and recombination operators from the earlier algorithm, we extended the algorithm with a separate archive (population). The archive continuously stores the new potential Pareto optimal solutions, when it becomes full, the algorithm deletes a part of the archive. The new version gives results which show a substantial improvement in quality over the earlier version and performs slightly better then NSGA II on the chosen test problems.