论文信息 - BBO-Benchmarking of the GLOBAL method for the Noiseless Function Testbed

BBO-Benchmarking of the GLOBAL method for the Noiseless Function Testbed

GLOBAL is a multistart type stochastic method for bound constrained global optimization problems. Its goal is to flnd all the local minima that are potentially global. For this reason it involves a combination of sampling, clustering, and local search. We report its results on the noisy free problems given.

Mihály Csaba Markót | A. Neumaier | T. Csendes | László Pál

[1] Alexander H. G. Rinnooy Kan,et al. A stochastic method for global optimization , 1982, Math. Program..

[2] Tibor Csendes,et al. Nonlinear Parameter Estimation by Global Optimization - Efficiency and reliability , 1989, Acta Cybern..

[3] Tibor Csendes,et al. Noname manuscript No. (will be inserted by the editor) The GLOBAL Optimization Method Revisited , 2022 .

[4] Raymond Ros,et al. Real-Parameter Black-Box Optimization Benchmarking 2009: Experimental Setup , 2009 .

[5] Anne Auger,et al. Real-Parameter Black-Box Optimization Benchmarking 2009: Noiseless Functions Definitions , 2009 .