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New classes of globally convexized filled functions for global optimization. (English) Zbl 1047.90051

Summary: We propose new classes of globally convexized filled functions. Unlike the globally convexized filled functions previously proposed in literature, the ones proposed in this paper are continuously differentiable and, under suitable assumptions, their unconstrained minimization allows to escape from any local minima of the original objective function. Moreover we show that the properties of the proposed functions can be extended to the case of box constrained minimization problems. We also report the results of a preliminary numerical experience.

MSC:

90C26 Nonconvex programming, global optimization
90C30 Nonlinear programming

Software:

SDBOX
Full Text: DOI