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.
Reviewer: Jiří Rohn (Praha)
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 |