Results 1 to 10 of about 1,802,858 (209)
An active-set algorithm for solving large-scale nonsmooth optimization models with box constraints. [PDF]
PLoS ONE, 2018 It is well known that the active set algorithm is very effective for smooth box constrained optimization. Many achievements have been obtained in this field.
Yong Li, Gonglin Yuan, Zhou Sheng
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Data-Driven Nonsmooth Optimization [PDF]
SIAM Journal on Optimization, 2020 In this work, we consider methods for solving large-scale optimization problems with a possibly nonsmooth objective function. The key idea is to first specify a class of optimization algorithms using a generic iterative scheme involving only linear operations and applications of proximal operators.
Sebastian Banert +4 more
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On solving elliptic obstacle problems by constant abs-linearization
Results in Control and Optimization, 2023 We consider optimal control problems governed by an elliptic variational inequality of the first kind, namely the obstacle problem. The variational inequality is treated by penalization, which leads to optimization problems governed by a nonsmooth semi ...
Olga Weiß, Monika Weymuth
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Existence of Solutions for Nonconvex and Nonsmooth Vector Optimization Problems
Journal of Inequalities and Applications, 2008 We consider the weakly efficient solution for a class of nonconvex and nonsmooth vector optimization problems in Banach spaces. We show the equivalence between the nonconvex and nonsmooth vector optimization problem and the vector variational-like ...
Nan-Jing Huang +2 more
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Complexity, 2021 For enhancing the stability of the microgrid operation, this paper proposes an optimization model considering the small-signal stability constraint.
Peijie Li +3 more
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Algorithms, 2020 Nonsmooth optimization refers to the general problem of minimizing (or maximizing) functions that have discontinuous gradients. This Special Issue contains six research articles that collect together the most recent techniques and applications in the ...
Napsu Karmitsa, Sona Taheri
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Open Journal of Mathematical Optimization, 2023 Frank and Wolfe’s celebrated conditional gradient method is a well-known tool for solving smooth optimization problems for which minimizing a linear function over the feasible set is computationally cheap.
de Oliveira, Welington
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Guignard Qualifications and Stationary Conditions for Mathematical Programming with Nonsmooth Switching Constraints [PDF]
Control and Optimization in Applied Mathematics, 2021 In this paper, some constraint qualifications of the Guignard type are defined for optimization problems with continuously differentiable objective functions and locally Lipschitz switching constraints.
Fatemeh Gorgini Shabankareh +3 more
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Asymptotic stationarity and regularity for nonsmooth optimization problems [PDF]
Journal of Nonsmooth Analysis and Optimization, 2020 Based on the tools of limiting variational analysis, we derive a sequential necessary optimality condition for nonsmooth mathematical programs which holds without any additional assumptions. In order to ensure that stationary points in this new sense are
Patrick Mehlitz
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Essentials of numerical nonsmooth optimization [PDF]
4OR, 2019 AbstractApproximately sixty years ago two seminal findings, the cutting plane and the subgradient methods, radically changed the landscape of mathematical programming. They provided, for the first time, the practical chance to optimize real functions of several variables characterized by kinks, namely by discontinuities in their derivatives.
Gaudioso, Manlio +2 more
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