On an efficient use of gradient information for accelerating interval global optimization algorithms
The authors present a branch-and-bound type algorithm for finding all global minima of a real-valued function \(f\) over an interval (box) \(S\) in \(\mathbb{R}^n\). The main contribution is an improved formula for computing a lower bound of \(f\) over a subinterval of \(S\) based on a refined use of gradient information.
scientific article