On strong homogeneity of two global optimization algorithms based on statistical models of multimodal objective functions

Details On strong homogeneity of two global optimization algorithms based on statistical models of multimodal objective functions On strong homogeneity of two global optimization algorithms based on statistical models of multimodal objective functions

2011-08-04

arxiv.org/abs/1108.1042v1

Computer Science

Numerical Analysis

11 pages, 1 figure

Scientific paper

10.1016/j.amc.2011.07.051

The implementation of global optimization algorithms, using the arithmetic of
in?nity, is considered. A relatively simple version of implementation is
proposed for the algorithms that possess the introduced property of strong
homogeneity. It is shown that the P-algorithm and the one-step Bayesian
algorithm are strongly homogeneous.

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