An Analysis of a Hybrid Optimization Method for Variational Data Assimilation

DOI10.1080/1061856031000120510zbMath1161.76449OpenAlexW2108488489MaRDI QIDQ4456960

I. Michael Navon, Dacian N. Daescu

Publication date: 21 March 2004

Published in: International Journal of Computational Fluid Dynamics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/1061856031000120510

zbMATH Keywords

OptimizationData assimilationHessian-free NewtonLimited memory L-BFGS

Mathematics Subject Classification ID

Numerical optimization and variational techniques (65K10) Water waves, gravity waves; dispersion and scattering, nonlinear interaction (76B15) Internal waves for incompressible inviscid fluids (76B55)

Related Items (6)

Aerodynamic shape optimization using first and second order adjoint and direct approaches ⋮ Optimal reduced space for variational data assimilation ⋮ The continuous direct-adjoint approach for second-order sensitivities in viscous aerodynamic inverse design problems ⋮ Discrete second order adjoints in atmospheric chemical transport modeling ⋮ Second-order adjoints for solving PDE-constrained optimization problems ⋮ Criteria of optimality for sensors' location based on adjoint transformation of observation data interpolation error

Uses Software

• TNPACK
• PREQN
• L-BFGS
• ARPACK
• tn
• chammp

Cites Work

• Some numerical experiments with variable-storage quasi-Newton algorithms
• On the limited memory BFGS method for large scale optimization
• Assessing a search direction within a truncated Newton method
• A standard test set for numerical approximations to the shallow water equations in spherical geometry
• The adjoint Newton algorithm for large-scale unconstrained optimization in meteorology applications
• Representations of quasi-Newton matrices and their use in limited memory methods
• A truncated Newton optimization algorithm in meteorology applications with analytic Hessian/vector products
• Numerical Experience with Limited-Memory Quasi-Newton and Truncated Newton Methods
• Preconditioning of Truncated-Newton Methods
• Updating Quasi-Newton Matrices with Limited Storage
• Inexact Newton Methods
• A Numerical Study of the Limited Memory BFGS Method and the Truncated-Newton Method for Large Scale Optimization
• Numerical Optimization
• TNPACK—A truncated Newton minimization package for large-scale problems
• ARPACK Users' Guide
• Automatic Preconditioning by Limited Memory Quasi-Newton Updating
• Algorithm 809: PREQN
• Enriched methods for large-scale unconstrained optimization

This page was built for publication: An Analysis of a Hybrid Optimization Method for Variational Data Assimilation