Heuristic Rejection in Interval Global Optimization

L.G. Casado, I. García, T. Csendes and V.G. Ruíz
Additional contact information
L.G. Casado: University of Almería
I. García: University of Almería
T. Csendes: University of Szeged
V.G. Ruíz: University of Almería

Journal of Optimization Theory and Applications, 2003, vol. 118, issue 1, No 2, 27-43

Abstract: Abstract Based on the investigation carried out in Ref. 1, this paper incorporates new studies about the properties of inclusion functions on subintervals while a branch-and-bound algorithm is solving global optimization problems. It is found that the relative place of the global minimum value within the inclusion function value of the objective function at the current interval indicates mostly whether the given interval is close to a minimizer point. This information is used in a heuristic interval rejection rule that can save a considerable amount of computation. Illustrative examples are discussed and an extended numerical study shows the advantages of the new approach.

Keywords: Interval method; global optimization; branch-and-bound algorithms (search for similar items in EconPapers)
Date: 2003
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DOI: 10.1023/A:1024731306785

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