Results 81 to 90 of about 22,374 (199)

Variational Optimality Conditions with Feedback Descent Controls that Strengthen the Maximum Principle

Известия Иркутского государственного университета: Серия "Математика", 2014
We derive nonlocal necessary optimality conditions that strengthen both classical and nonsmooth Maximum Principles for nonlinear optimal control problems with free right-hand end of trajectories.
V.A. Dykhta
doaj  

On a Monotone Scheme for Nonconvex Nonsmooth Optimization with Applications to Fracture Mechanics. [PDF]

J Optim Theory Appl, 2019
Ghilli D, Ghilli D, Kunisch K.
europepmc   +1 more source

The NFDA-Nonsmooth Feasible Directions Algorithm applied to construction of Pareto Fronts of Ridge and Lasso Regressions

Trends in Computational and Applied Mathematics
Ridge and Lasso regressions are types of linear regression, a machine learning tool for dealing with data. Based on multiobjective optimization theory, we transform Ridge and Lasso regression into bi-objective optimization problems. The Pareto fronts of
W. P. Freire
doaj   +1 more source

The Modified HZ Conjugate Gradient Algorithm for Large-Scale Nonsmooth Optimization. [PDF]

PLoS One, 2016
Yuan G, Sheng Z, Liu W.
europepmc   +1 more source

A modified inertial proximal alternating direction method of multipliers with dual-relaxed term for structured nonconvex and nonsmooth problem

Journal of Inequalities and Applications
In this research, we introduce a novel optimization algorithm termed the dual-relaxed inertial alternating direction method of multipliers (DR-IADM), tailored for handling nonconvex and nonsmooth problems. These problems are characterized by an objective
Yang Liu, Long Wang, Yazheng Dang
doaj   +1 more source

Signal and Information Processing in Networks. [PDF]

Entropy (Basel), 2023
Feng M, Deng LJ, Chen F.
europepmc   +1 more source

A modified inertial proximal minimization algorithm for structured nonconvex and nonsmooth problem

Journal of Inequalities and Applications
We introduce an enhanced inertial proximal minimization algorithm tailored for a category of structured nonconvex and nonsmooth optimization problems.
Zhonghui Xue, Qianfeng Ma
doaj   +1 more source

NonOpt: Nonconvex, Nonsmooth Optimizer

NonOpt, a C++ software package for minimizing locally Lipschitz objective functions, is presented. The software is intended primarily for minimizing objective functions that are nonconvex and/or nonsmooth. The package has implementations of two main algorithmic strategies: a gradient-sampling and a proximal-bundle method.
Curtis, Frank E., Zebiane, Lara
openaire   +2 more sources

A new method for nonsmooth convex optimization

Journal of Inequalities and Applications, 1998
A new method for minimizing a proper closed convex function is proposed and its convergence properties are studied. The convergence rate depends on both the growth speed off at minimizers and the choice of proximal parameters.
Birge JR, Wel Z, Qi L
doaj  

M-PSGP: a momentum-based proximal scaled gradient projection algorithm for nonsmooth optimization with application to image deblurring. [PDF]

Front Big Data
Ning K, Lü Q, Liao X.
europepmc   +1 more source