Maintaining the positive definiteness of the matrices in reduced secant methods for equality constrained optimization
From MaRDI portal
Publication:2641222
DOI10.1007/BF01594922zbMath0721.90068OpenAlexW2074899569MaRDI QIDQ2641222
Publication date: 1991
Published in: Mathematical Programming. Series A. Series B (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/bf01594922
Nonlinear programming (90C30) Computational methods for problems pertaining to operations research and mathematical programming (90-08)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Minimizing a differentiable function over a differential manifold
- A globally convergent method for nonlinear programming
- Minimization of functions having Lipschitz continuous first partial derivatives
- Variants of the reduced Newton method for nonlinear equality constrained optimization problems
- An only 2-step Q-superlinear convergence example for some algorithms that use reduced hessian approximations
- On the Local Convergence of a Quasi-Newton Method for the Nonlinear Programming Problem
- An example of irregular convergence in some constrained optimization methods that use the projected hessian
- Projected Hessian Updating Algorithms for Nonlinearly Constrained Optimization
- Continuity of the null space basis and constrained optimization
- On the local and global convergence of a reduced Quasi-Newton method1
- Asymptotic Admissibility of the Unit Stepsize in Exact Penalty Methods
- Exact penalty functions in nonlinear programming
- Reduced quasi-Newton methods with feasibility improvement for nonlinearly constrained optimization
- A surperlinearly convergent algorithm for constrained optimization problems
- Nonlinear programming via an exact penalty function: Global analysis
- Nonlinear programming via an exact penalty function: Asymptotic analysis
- Optimal conditioning of self-scaling variable Metric algorithms
- Quasi-Newton Methods, Motivation and Theory
- Superlinearly convergent variable metric algorithms for general nonlinear programming problems
- Matrix conditioning and nonlinear optimization
- Algorithms for nonlinear constraints that use lagrangian functions
- Convergence Conditions for Ascent Methods
