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On a new stochastic global optimization algorithm based on censored observations |
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| Authors: | Fabio Schoen |
| Institution: | (1) Department of Computer Sciences, University of Milano, via Comelico 39/41, I-20135 Milano, Italy |
| Abstract: | In this paper a new algorithm is proposed for global optimization problems. The main idea is that of modifying a standard clustering approach by sequentially sampling the objective function while adaptively deciding an appropriate sample size. Theoretical as well as computational results are presented. |
| Keywords: | Global optimization Multistart algorithm sequential stopping rules nonparametric models clustering techniques censored observations |
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