“…This generalization is based on the dimensionality-free convergence investigations of Chapter 2.2: for this reason, the approach is essentially independent of the original one-dimensional function class models which served as the basis of the corresponding univariate global optimization algorithms. It should be noted at this point that diverse, more specific generalizations and diverse extensions of Piyavskii's univariate algorithm are discussed, for example, by Mayne and Polak (1984), Galperin (1985Galperin ( , 1987Galperin ( , 1988, Mladineo (1986Mladineo ( , 1992a, Strigul (1987), Nefedov (1987), Shepilov (1987), Mayne (1988, 1989), Korotkich (1989), Wood (1991Wood ( , 1992 and Zhang, Wood and Baritompa (1993). Additionally, semi-heuristic multivariate extensions of one-dimensional statistical function models are reviewed and discussed, for example, by Mockus (1989) and Zilinskas (1982Zilinskas ( , 1992.…”