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On an efficient use of gradient information for accelerating interval global optimization algorithms. (English) Zbl 1078.65053

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.

MSC:

65K05 Numerical mathematical programming methods
65G40 General methods in interval analysis
90C26 Nonconvex programming, global optimization
90C57 Polyhedral combinatorics, branch-and-bound, branch-and-cut

Software:

INTOPT_90
Full Text: DOI