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

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Article ID: iaor20123328
Volume: 218
Issue: 16
Start Page Number: 8131
End Page Number: 8136
Publication Date: Apr 2012
Journal: Applied Mathematics and Computation
Authors:
Keywords: statistics: inference
Abstract:

The implementation of global optimization algorithms, using the arithmetic of infinity, 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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