The convergence speed of interval methods for global optimization

Three particular algorithms from a class of interval subdivision methods for global optimization are studied. The theoretical upper bound on the convergence speed of Hansen's method is given. The three methods (by Hansen, Moore-Skelboe, and a new one with a random actual box selection rule) are...

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Bibliographic Details
Published in:	Computers & mathematics with applications (1987) Vol. 31; no. 4; pp. 173 - 178
Main Authors:	Csallner, A.E., Csendes, T.
Format:	Journal Article Conference Proceeding
Language:	English
Published:	Oxford Elsevier Ltd 01-02-1996 Elsevier
Subjects:	Applied sciences Exact sciences and technology Global optimization Interval arithmetic Operational research and scientific management Operational research. Management science Optimization. Search problems Subdivision Global optimization Interval arithmetic Subdivision Upper bound Unconstrained optimization N variable function Iterative method Global optimum Objective function Selection rule Convergence speed
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Summary:	Three particular algorithms from a class of interval subdivision methods for global optimization are studied. The theoretical upper bound on the convergence speed of Hansen's method is given. The three methods (by Hansen, Moore-Skelboe, and a new one with a random actual box selection rule) are compared numerically.
ISSN:	0898-1221 1873-7668
DOI:	10.1016/0898-1221(95)00229-4