STRSCNE

A Matlab solver for constrained nonlinear equations is presented. The code, called STRSCNE, is based on the affine scaling trust-region method STRN, recently proposed by the authors. The approach taken in implementing the key steps of the method is discussed. The structure and the usage of STRSCNE are described and its features and capabilities are illustrated by numerical experiments. The results of a comparison with high quality codes for nonlinear optimization are shown.


References in zbMATH (referenced in 52 articles , 1 standard article )

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  1. Abubakar, Auwal Bala; Kumam, Poom; Mohammad, Hassan: A note on the spectral gradient projection method for nonlinear monotone equations with applications (2020)
  2. Gonçalves, M. L. N.; Oliveira, F. R.: On the global convergence of an inexact quasi-Newton conditional gradient method for constrained nonlinear systems (2020)
  3. Gu, Ran; Yuan, Ya Xiang: A partial first-order affine-scaling method (2019)
  4. Kimiaei, Morteza; Rahpeymaii, Farzad: A new nonmonotone line-search trust-region approach for nonlinear systems (2019)
  5. Rahpeymaii, Farzad: An efficient conjugate gradient trust-region approach for systems of nonlinear equation (2019)
  6. Sanguinetti, Guido (ed.); Huynh-Thu, Vân Anh (ed.): Gene regulatory networks. Methods and protocols (2019)
  7. Zhao, Lijuan: Nonmonotone conic trust region method with line search technique for bound constrained optimization (2019)
  8. Galli, Leonardo; Kanzow, Christian; Sciandrone, Marco: A nonmonotone trust-region method for generalized Nash equilibrium and related problems with strong convergence properties (2018)
  9. Gonçalves, M. L. N.; Oliveira, F. R.: An inexact Newton-like conditional gradient method for constrained nonlinear systems (2018)
  10. Marini, Leopoldo; Morini, Benedetta; Porcelli, Margherita: Quasi-Newton methods for constrained nonlinear systems: complexity analysis and applications (2018)
  11. Morini, Benedetta; Porcelli, Margherita; Toint, Philippe L.: Approximate norm descent methods for constrained nonlinear systems (2018)
  12. Gonçalves, Max L. N.; Melo, Jefferson G.: A Newton conditional gradient method for constrained nonlinear systems (2017)
  13. Kimiaei, Morteza: A new class of nonmonotone adaptive trust-region methods for nonlinear equations with box constraints (2017)
  14. Amini, Keyvan; Shiker, Mushtak A. K.; Kimiaei, Morteza: A line search trust-region algorithm with nonmonotone adaptive radius for a system of nonlinear equations (2016)
  15. Dumbser, M.; Facchini, M.: A space-time discontinuous Galerkin method for Boussinesq-type equations (2016)
  16. Wang, X. Y.; Li, S. J.; Kou, Xi Peng: A self-adaptive three-term conjugate gradient method for monotone nonlinear equations with convex constraints (2016)
  17. Li, Xiangli: Smoothing nonmonotone Barzilai-Borwein gradient method and its application to stochastic linear complementarity problems (2015)
  18. Ling, Chen; Wang, Guifeng; He, Hongjin: A new Levenberg-Marquardt type algorithm for solving nonsmooth constrained equations (2014)
  19. Porcelli, Margherita: On the convergence of an inexact Gauss-Newton trust-region method for nonlinear least-squares problems with simple bounds (2013)
  20. Wang, Xiao: A trust region affine scaling method for bound constrained optimization (2013)

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