NEWUOA
NEWUOA is a software developped by M.J.D. Powell for unconstrained optimization without derivatives. The NEWUOA seeks the least value of a function F(x) (x is a vector of dimension n ) when F(x) can be calculated for any vector of variables x . The algorithm is iterative, a quadratic model being required at the beginning of each iteration, which is used in a trust region procedure for adjusting the variables. When the quadratic model is revised, the new model interpolates F at m points, the value m=2n+1 being recommended.
Keywords for this software
References in zbMATH (referenced in 96 articles )
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- Brás, C. P.; Custódio, A. L.: On the use of polynomial models in multiobjective directional direct search (2020)
- Gumma, E. A. E.; Ali, M. Montaz; Hashim, M. H. A.: A derivative-free algorithm for non-linear optimization with linear equality constraints (2020)
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- Xi, Min; Sun, Wenyu; Chen, Jun: Survey of derivative-free optimization (2020)
- Xi, Min; Sun, Wenyu; Chen, Yannan; Sun, Hailin: A derivative-free algorithm for spherically constrained optimization (2020)
- Ahmadvand, Mohammad; Esmaeilbeigi, Mohsen; Kamandi, Ahmad; Yaghoobi, Farajollah Mohammadi: An improved hybrid-ORBIT algorithm based on point sorting and MLE technique (2019)
- Berahas, Albert S.; Byrd, Richard H.; Nocedal, Jorge: Derivative-free optimization of noisy functions via quasi-Newton methods (2019)
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- Cartis, Coralia; Roberts, Lindon: A derivative-free Gauss-Newton method (2019)