Improved Hessian approximation with modified secant equations for symmetric rank-one method

DOI10.1016/j.cam.2010.10.042zbMath1209.65062OpenAlexW1972453316MaRDI QIDQ629505

Abu Hassan Malik, Wah June Leong, Farzin Modarres

Publication date: 9 March 2011

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cam.2010.10.042

zbMATH Keywords

algorithmsnumerical resultsunconstrained minimizationquasi-Newton methodssecant equationHessian approximationsymmetric rank-one update

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Methods of quasi-Newton type (90C53)

Related Items (6)

Quasi-Newton methods based on ordinary differential equation approach for unconstrained nonlinear optimization ⋮ On the performance of a new symmetric rank-one method with restart for solving unconstrained optimization problems ⋮ Limited memory methods with improved symmetric rank-one updates and its applications on nonlinear image restoration ⋮ A symmetric rank-one method based on extra updating techniques for unconstrained optimization ⋮ Scaled memoryless symmetric rank one method for large-scale optimization ⋮ A sufficient descent three-term conjugate gradient method via symmetric rank-one update for large-scale optimization

Uses Software

• CUTEr
• CUTE

Cites Work

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• Sizing and Least-Change Secant Methods
• Optimal Conditioning and Convergence in Rank One Quasi-Newton Updates
• CUTE
• Eigenvalues and switching algorithms for Quasi-Newton updates
• A Theoretical and Experimental Study of the Symmetric Rank-One Update
• A new approach to symmetric rank-one updating
• A modified BFGS method and its global convergence in nonconvex minimization
• A modified rank one update which converges \(Q\)-superlinearly
• Benchmarking optimization software with performance profiles.

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