On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems
Rook J, Trautmann H, Bossek J, Grimme C
Hardness of Multi-Objective (MO) continuous optimization problems results from an interplay of various problem characteristics, e. g. the degree of multi-modality. We present a benchmark study of classical and diversity focused optimizers on multi-modal MO problems based on automated algorithm configuration. We show the large effect of the latter and investigate the trade-off between convergence in objective space and diversity in decision space.
multi-objective optimization; configuration; multi-modality