Abstract

ABSTRACT In this paper, we consider convex underestimators for univariate nonconvex functions over an interval in R . We propose a new convex underestimator that can be used for computing the lower bound of the range of nonconvex functions, or for solving global optimization problems. We show that the new underestimator is tighter than other underestimators which are developed in the literature.

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