In numerical optimization, meta-optimization is the use of one optimization method to tune another optimization method. Meta-optimization is reported to have been used as early as in the late 1970s by Mercer and Sampson [1] for finding optimal parameter settings of a genetic algorithm. Meta-optimization is also known in the literature as meta-evolution, super-optimization, automated parameter calibration, hyper-heuristics, etc.