A robust BFGS algorithm for unconstrained nonlinear optimization problems
From MaRDI portal
Publication:6151643
DOI10.1080/02331934.2022.2124869MaRDI QIDQ6151643
Publication date: 11 March 2024
Published in: Optimization (Search for Journal in Brave)
Cites Work
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- Robust optimal solutions in interval linear programming with forall-exists quantifiers
- A globally and quadratically convergent algorithm with efficient implementation for unconstrained optimization
- A new approach to uncertain parameter linear programming
- Adjustable robust solutions of uncertain linear programs
- Robust aspects of solutions in deterministic multiple objective linear programming
- Linear Programming under Uncertainty
- Theory and Applications of Robust Optimization
- Worst-Case Value-At-Risk and Robust Portfolio Optimization: A Conic Programming Approach
- Updating Quasi-Newton Matrices with Limited Storage
- Numerical Optimization
- Convergence Properties of the BFGS Algoritm
- A New Conjugate Gradient Method with Guaranteed Descent and an Efficient Line Search
- The Limited Memory Conjugate Gradient Method
- Convergence Conditions for Ascent Methods
- Convergence Conditions for Ascent Methods. II: Some Corrections
- Globally convergent algorithms for robust pole assignment by state feedback
- Benchmarking optimization software with performance profiles.