Global Optimization Test
Global Optimization Test Problems. Many test problems are presented here in order to examine the performance of global optimization methods. The behavior of these test problems varies to cover most difficulties faced in the area of continuous global optimization. The presented problems are: Test Functions for Unconstrained Global Optimization. Test Problems for Constrained Global Optimization.
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References in zbMATH (referenced in 6 articles )
Showing results 1 to 6 of 6.
- Hladík, Milan: An extension of the $\alpha\mathrmBB$-type underestimation to linear parametric Hessian matrices (2016)
- Bofill, Josep Maria; Quapp, Wolfgang; Bernuz, Efrem: Some remarks on the model of the extended gentlest ascent dynamics (2015)
- Kocuk, Burak; Altınel, İ. Kuban; Aras, Necati: Approximating the objective function’s gradient using perceptrons for constrained minimization with application in drag reduction (2015)
- Liu, Qunfeng; Zeng, Jinping; Yang, Gang: MrDIRECT: a multilevel robust DIRECT algorithm for global optimization problems (2015)
- Wei, Fei; Wang, Yuping; Lin, Hongwei: A new filled function method with two parameters for global optimization (2014)
- Li, Genzi; Aute, Vikrant; Azarm, Shapour: An accumulative error based adaptive design of experiments for offline metamodeling (2010)