Global optimization of expensive black box problems with a known lower bound

Andrea Cassioli () and Fabio Schoen ()

Journal of Global Optimization, 2013, vol. 57, issue 1, 177-190

Abstract: In this paper we propose an algorithm for the global optimization of computationally expensive black–box functions. For this class of problems, no information, like e.g. the gradient, can be obtained and function evaluation is highly expensive. In many applications, however, a lower bound on the objective function is known; in this situation we derive a modified version of the algorithm introduced in Gutmann (J Glob Optim 19:201–227, 2001 ). Using this information produces a significant improvement in the quality of the resulting method, with only a small increase in the computational cost. Extensive computational results are provided which support this statement. Copyright Springer Science+Business Media, LLC. 2013

Keywords: Global optimization; Black-box function; Expensive objective functions; Radial basis method; Bumpiness (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10898-011-9834-7

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