DGM is a Fortran implementation of the discrete gradient method for derivative free optimization. To apply DGM, one only needs to compute at every point the value of the objective function. The subgradient will be approximated. The software is free for academic teaching and research purposes but I ask you to refer the reference given below if you use it.
Keywords for this software
References in zbMATH (referenced in 29 articles , 1 standard article )
Showing results 21 to 29 of 29.
- Mahdavi-Amiri, Nezam; Yousefpour, Rohollah: An effective nonsmooth optimization algorithm for locally Lipschitz functions (2012)
- Bagirov, A. M.; Ugon, J.: Codifferential method for minimizing nonsmooth DC functions (2011)
- Bagirov, Adil; Clausen, Conny; Kohler, Michael: An algorithm for the estimation of a regression function by continuous piecewise linear functions (2010)
- Bagirov, Adil M.; Ganjehlou, Asef Nazari: A quasisecant method for minimizing nonsmooth functions (2010)
- Gaudioso, Manlio; Gorgone, Enrico: Gradient set splitting in nonconvex nonsmooth numerical optimization (2010)
- Gaudioso, M.; Gorgone, E.; Pallaschke, D.: Separation of convex sets by Clarke subdifferential (2010)
- Kiwiel, K. C.: Improved convergence result for the discrete gradient and secant methods for nonsmooth optimization (2010)
- Bagirov, Adil; Ganjehlou, Asef Nazari: An approximate subgradient algorithm for unconstrained nonsmooth, nonconvex optimization (2008)
- Bagirov, A. M.; Karasözen, B.; Sezer, M.: Discrete gradient method: Derivative-free method for nonsmooth optimization (2008)