New interval methods for constrained global optimization

New interval methods for constrained global optimization

Interval analysis is a powerful tool which allows to design branch-and-bound algorithms able to solve many global optimization problems. In this paper we present new adaptive multisection rules which enable the algorithm to choose the proper multisection type depending on simple heuristic decision r...

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Bibliographic Details
Published in:Mathematical programming Vol. 106; no. 2; pp. 287 - 318
Main Authors: MARKOT, M. Cs, FERNANDEZ, J, CASADO, L. G, CSENDES, T
Format: Journal Article
Language:English
Published: Heidelberg Springer 01-06-2006
Springer Nature B.V
Subjects:
Algorithms
Applied sciences
Boxes
Branch & bound algorithms
Exact sciences and technology
Flows in networks. Combinatorial problems
Heuristic
Mathematical functions
Mathematical programming
Operational research and scientific management
Operational research. Management science
Optimization
Studies
Interval analysis
Interval analysis -Adaptive multisection
Global optimization
Branch and bound method
Computational study
Selection criterion
Global optimum
Inequality constrained problems
Subinterval selection criterion
Constrained optimization
Mathematical programming
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Summary:Interval analysis is a powerful tool which allows to design branch-and-bound algorithms able to solve many global optimization problems. In this paper we present new adaptive multisection rules which enable the algorithm to choose the proper multisection type depending on simple heuristic decision rules. Moreover, for the selection of the next box to be subdivided, we investigate new criteria. Both the adaptive multisection and the subinterval selection rules seem to be specially suitable for being used in inequality constrained global optimization problems. The usefulness of these new techniques is shown by computational studies. [PUBLICATION ABSTRACT]
ISSN:0025-5610
1436-4646
DOI:10.1007/s10107-005-0607-2