A new infeasible proximal bundle algorithm for nonsmooth nonconvex constrained optimization
Sign Up to like & getrecommendations! Published in 2019 at "Computational Optimization and Applications"
DOI: 10.1007/s10589-019-00115-8
Abstract: Proximal bundle method has usually been presented for unconstrained convex optimization problems. In this paper, we develop an infeasible proximal bundle method for nonsmooth nonconvex constrained optimization problems. Using the improvement function we transform the… read more here.
Keywords: infeasible proximal; proximal bundle; nonconvex constrained; constrained optimization ... See more keywords
Convergence rates for an inexact linearized ADMM for nonsmooth nonconvex optimization with nonlinear equality constraints
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DOI: 10.1007/s10589-025-00737-1
Abstract: In this paper, we consider nonconvex optimization problems with nonsmooth nonconvex objective function and nonlinear equality constraints. We assume that both the objective function and the functional constraints can be separated into 2 blocks. To… read more here.
Keywords: optimization; nonsmooth nonconvex; convergence; equality constraints ... See more keywords
A Proximal-Type Method for Nonsmooth and Nonconvex Constrained Minimization Problems
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DOI: 10.1007/s10957-024-02597-x
Abstract: This work proposes an implementable proximal-type method for a broad class of optimization problems involving nonsmooth and nonconvex objective and constraint functions. In contrast to existing methods that rely on an ad hoc model approximating… read more here.
Keywords: type method; model; nonsmooth nonconvex; proximal type ... See more keywords
A mixed noise removal algorithm based on multi-fidelity modeling with nonsmooth and nonconvex regularization
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DOI: 10.1007/s11042-019-7625-1
Abstract: In this article, we propose a mixed-noise removal model which incorporates with a nonsmooth and nonconvex regularizer. To solve this model, a multistage convex relaxation method is used to deal with the optimization problem due… read more here.
Keywords: noise removal; mixed noise; model; noise ... See more keywords
Convergence of a stochastic subgradient method with averaging for nonsmooth nonconvex constrained optimization
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DOI: 10.1007/s11590-020-01537-8
Abstract: We prove convergence of a single time-scale stochastic subgradient method with subgradient averaging for constrained problems with a nonsmooth and nonconvex objective function having the property of generalized differentiability. As a tool of our analysis,… read more here.
Keywords: subgradient method; subgradient; stochastic subgradient; optimization ... See more keywords
Lagrange multiplier characterizations of constrained best approximation with nonsmooth nonconvex constraints
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DOI: 10.2298/fil2014669m
Abstract: In this paper, we consider the constraint set K := {x ? Rn : gj(x)? 0,? j = 1,2,...,m} of inequalities with nonsmooth nonconvex constraint functions gj : Rn ? R (j = 1,2,...,m).We show… read more here.
Keywords: best approximation; lagrange multiplier; constrained best; constraint ... See more keywords