An active-set projected trust-region algorithm with limited memory BFGS technique for box-constrained nonsmooth equations
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Publication:2868903
DOI10.1080/02331934.2011.603321zbMath1278.65092OpenAlexW2079585877MaRDI QIDQ2868903
Liqun Qi, Gong Lin Yuan, Zeng-xin Wei
Publication date: 19 December 2013
Published in: Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/02331934.2011.603321
Numerical mathematical programming methods (65K05) Nonconvex programming, global optimization (90C26)
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Cites Work
- An active set limited memory BFGS algorithm for bound constrained optimization
- Limited memory BFGS method with backtracking for symmetric nonlinear equations
- Active-set projected trust-region algorithm for box-constrained nonsmooth equations
- Finite-dimensional variational inequality and nonlinear complementarity problems: A survey of theory, algorithms and applications
- Some numerical experiments with variable-storage quasi-Newton algorithms
- On the limited memory BFGS method for large scale optimization
- An active set limited memory BFGS algorithm for large-scale bound constrained optimization
- BFGS trust-region method for symmetric nonlinear equations
- A new backtracking inexact BFGS method for symmetric nonlinear equations
- New constrained optimization reformulation of complementarity problems
- A QP-free constrained Newton-type method for variational inequality problems
- Representations of quasi-Newton matrices and their use in limited memory methods
- On unconstrained and constrained stationary points of the implicit Lagrangian
- A feasible semismooth asymptotically Newton method for mixed complementarity problems
- Nonmonotone backtracking inexact quasi-Newton algorithms for solving smooth nonlinear equations
- An affine scaling trust-region approach to bound-constrained nonlinear systems
- Nonmonotone Trust-Region Methods for Bound-Constrained Semismooth Equations with Applications to Nonlinear Mixed Complementarity Problems
- Regular Pseudo-Smooth NCP and BVIP Functions and Globally and Quadratically Convergent Generalized Newton Methods for Complementarity and Variational Inequality Problems
- Nonsmooth Equations: Motivation and Algorithms
- MODIFIED LIMITED MEMORY BFGS METHOD WITH NONMONOTONE LINE SEARCH FOR UNCONSTRAINED OPTIMIZATION
- Projected gradient methods for linearly constrained problems
- A subspace limited memory quasi-Newton algorithm for large-scale nonlinear bound constrained optimization
- Engineering and Economic Applications of Complementarity Problems
- Solving Karush--Kuhn--Tucker Systems via the Trust Region and the Conjugate Gradient Methods
- Convergence Analysis of Some Algorithms for Solving Nonsmooth Equations
- A Limited Memory Algorithm for Bound Constrained Optimization
- Strictly feasible equation-based methods for mixed complementarity problems
