An infeasible QP-free algorithm without a penalty function or a filter for nonlinear inequality-constrained optimization
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Publication:2926081
DOI10.1080/10556788.2013.879587zbMath1306.90151OpenAlexW2070433501MaRDI QIDQ2926081
Pu, Dingguo, Chungen Shen, Xiaojing Zhu, Weiai Liu
Publication date: 29 October 2014
Published in: Optimization Methods and Software (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/10556788.2013.879587
global convergencesuperlinear convergenceworking setfilter-freepenalty-function-freeinfeasible QP-free method
Related Items (2)
A QP-free algorithm without a penalty function or a filter for nonlinear general-constrained optimization ⋮ A smooth QP-free algorithm without a penalty function or a filter for mathematical programs with complementarity constraints
Cites Work
- Unnamed Item
- Sequential systems of linear equations method for general constrained optimization without strict complementarity
- Globally and superlinearly convergent QP-free algorithm for nonlinear constrained optimization
- Global convergence of a robust filter SQP algorithm
- A feasible QP-free algorithm combining the interior-point method with active set for constrained optimization
- An interior-point algorithm for nonconvex nonlinear programming
- A QP-free constrained Newton-type method for variational inequality problems
- Inertia-controlling factorizations for optimization algorithms
- A New QP-Free, Globally Convergent, Locally Superlinearly Convergent Algorithm For Inequality Constrained Optimization
- A Sequential Quadratic Programming Method Without A Penalty Function or a Filter for Nonlinear Equality Constrained Optimization
- A Feasible Active Set QP-Free Method for Nonlinear Programming
- A QP-Free, Globally Convergent, Locally Superlinearly Convergent Algorithm for Inequality Constrained Optimization
- Strongly Regular Generalized Equations
- Algorithms for nonlinear constraints that use lagrangian functions
- On the Accurate Identification of Active Constraints
- Numerical Optimization
- CUTE
- A Primal-Dual Interior-Point Method for Nonlinear Programming with Strong Global and Local Convergence Properties
- Trust Region Methods
- A Truncated Newton Algorithm for Large Scale Box Constrained Optimization
- SNOPT: An SQP Algorithm for Large-Scale Constrained Optimization
- Benchmarking optimization software with performance profiles.
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