Abstract
SEPA2+, one of the multi objective genetic algorithms, has two archives: one of them is for restoring the Pareto solutions that have the wide variety in the objective space and the other is for archiving the Pareto solutions that have the variety in the design variable space. In this paper, we examined the effect of two archives of SPEA2+ on solution search through the numerical examples. The results showed the following two tendencies: the archive for design variable helps to keep the diversity not only in the design variable space but also in the objective space and the diversity in the design variable space begins to maintain after the solutions are converged into local Pareto solutions. Inspiring these results, we proposed the new way how to use these two archives. In the proposed method, the population in the archive for objective function space is used for genetic operations until the number of the non-dominated solutions becomes bigger than the archive size. After that, the population in the archive for design variable space is used for genetic operations. In the comparison of the proposed method with SPEA2 and SPEA2+, the results of the proposed method showed the same precision of the derived Pareto solutions with the higher diversity in the design variable space.
