Chimera is a hiearchical ASF developed by Hase et al. Hiearchical means that the objectives are weighted, so the ASF will prioritise one objective over another. The main hyperparameters are the tolerances, which are values for each objective in [0, 1] that set how much each objective is weighted. A smaller tolerance indicates that the objective will be weighted more, while a larger tolerance indicates that the objective will be weighted less. The original paper does not give a clear mechanism for setting the tolerances, and the tolerances in the examples are tuned to the specific benchmarks used in the paper.