Local tuning and partition strategies for diagonal GO methods

Details Local tuning and partition strategies for diagonal GO methods Local tuning and partition strategies for diagonal GO methods

2011-03-18

arxiv.org/abs/1103.3665v1

Numerische Mathematik, 94(1), (2003) 93-106

Mathematics

Optimization and Control

15 pages, 4 figures

Scientific paper

In this paper, global optimization (GO) Lipschitz problems are considered where the multi-dimensional multiextremal objective function is determined over a hyperinterval. An efficient one-dimensional GO method using local tuning on the behavior of the objective function is generalized to the multi-dimensional case by the diagonal approach using two partition strategies. Global convergence conditions are established for the obtained diagonal geometric methods. Results of a wide numerical comparison show a strong acceleration reached by the new methods working with estimates of the local Lipschitz constants over different subregions of the search domain in comparison with the traditional approach.

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