Results 1 to 10 of about 24,030 (229)
A limited memory BFGS subspace algorithm for bound constrained nonsmooth problems
Journal of Inequalities and Applications, 2020 The subspace technique has been widely used to solve unconstrained/constrained optimization problems and there exist many results that have been obtained. In this paper, a subspace algorithm combining with limited memory BFGS update is proposed for large-
Xiangrong Li
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A Novel Approach for Solving Nonsmooth Optimization Problems with Application to Nonsmooth Equations
Journal of Mathematics, 2013 We present a new approach for solving nonsmooth optimization problems and a system of nonsmooth equations which is based on generalized derivative. For this purpose, we introduce the first order of generalized Taylor expansion of nonsmooth functions and
Hamid Reza Erfanian +2 more
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A modified three-term HS conjugate gradient method for solving nonsmooth minimizations
Journal of Hebei University of Science and Technology, 2018 To improve the efficiency for large-scale nonsmooth optimization problems and overcome the large storage requirements and complex computation of other algorithms, a modified HS conjugate gradient algorithm for nonsmooth optimization problems is proposed.
Yong LI, Songhua WANG
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International Journal of Applied Mathematics and Computer Science, 2023 A nonsmooth optimization control (NOC) based on a sandwich model with hysteresis is proposed to control a micropositioning system (MPS) with a piezoelectric actuator (PEA).
Yang Sen +3 more
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Balanced Circular Packing Problems with Distance Constraints
Computation, 2022 The packing of different circles in a circular container under balancing and distance conditions is considered. Two problems are studied: the first minimizes the container’s radius, while the second maximizes the minimal distance between circles, as well
Tetyana Romanova +6 more
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EURO Journal on Computational Optimization, 2015 Many real-world optimization models comprise nonconvex and nonsmooth functions leading to very hard classes of optimization models. In this article, a new interior-point method for the special, but practically relevant class of optimization problems with
Martin Schmidt
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One-Rank Linear Transformations and Fejer-Type Methods: An Overview
MathematicsSubgradient methods are frequently used for optimization problems. However, subgradient techniques are characterized by slow convergence for minimizing ravine convex functions.
Volodymyr Semenov +3 more
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Axioms, 2022 The nonconvex and nonsmooth optimization problem has been attracting increasing attention in recent years in image processing and machine learning research. The algorithm-based reweighted step has been widely used in many applications.
Juyeb Yeo, Myeongmin Kang
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A New Approach for Generalized Partial Derivatives of Non-smooth Functions
Walailak Journal of Science and Technology, 2014 In this paper, we define the functional optimization problems corresponding to multi-variable smooth functions, so that their optimal solutions are partial derivatives of these functions.
Hamid Reza ERFANIAN +2 more
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The Space Decomposition Theory for a Class of Semi-Infinite Maximum Eigenvalue Optimizations
Abstract and Applied Analysis, 2014 We study optimization problems involving eigenvalues of symmetric matrices. We present a nonsmooth optimization technique for a class of nonsmooth functions which are semi-infinite maxima of eigenvalue functions.
Ming Huang +3 more
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