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

Andrea Cassioli(cassioli***at***dsi.unifi.it)
Fabio Schoen(fabio.schoen***at***unifi.it)

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 in (Gutmann, 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.

Keywords: Global Optimization, black-box function, expensive objective functions, radial basis method, bumpiness

Category 1: Global Optimization

Category 2: Other Topics (Optimization of Simulated Systems )

Citation: submitted

Download: [PDF]

Entry Submitted: 07/15/2011
Entry Accepted: 07/15/2011
Entry Last Modified: 07/15/2011

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