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Abstract：
Robust analysis is important for designing and analyzing algorithm for global optimization. In this paper, we introduced a new concept, robust constant, to quantitatively characterize robustness of measurable sets and measurable functions. The new concept is consistent with the robustness proposed in literature. This paper also showed that robust constant had significant value in the analysis of some random search algorithms for solving global optimization problem.
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ADVANCES IN GLOBAL OPTIMIZATION
ISSN： 2194-1009
Year： 2015
Volume： 95
Page： 459-470
Language： English
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ESI Highly Cited Papers on the List： 0 Unfold All
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30 Days PV： 0
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