Partitioned variable metric updates for large structured optimization problems
From MaRDI portal
Publication:1162795
DOI10.1007/BF01399316zbMath0482.65035OpenAlexW2011253492WikidataQ57389758 ScholiaQ57389758MaRDI QIDQ1162795
Andreas Griewank, Phillipe L. Toint
Publication date: 1982
Published in: Numerische Mathematik (Search for Journal in Brave)
Full work available at URL: https://eudml.org/doc/132785
Related Items
An H-form variant of the partitioned QN method, Corrected sequential linear programming for sparse minimax optimization, Unnamed Item, New limited memory bundle method for large-scale nonsmooth optimization, Broyden's quasi-Newton methods for a nonlinear system of equations and unconstrained optimization: a review and open problems, A note on solving nonlinear optimization problems in variable precision, An SR1/BFGS SQP algorithm for nonconvex nonlinear programs with block-diagonal Hessian matrix, Unnamed Item, On large scale nonlinear network optimization, Approximate quasi-Newton methods, On the limited memory BFGS method for large scale optimization, Approximating Hessians in unconstrained optimization arising from discretized problems, Optimization techniques for tree-structured nonlinear problems, Sparse quasi-Newton updates with positive definite matrix completion, The global convergence of partitioned BFGS on problems with convex decompositions and Lipschitzian gradients, Convergence of quasi-Newton matrices generated by the symmetric rank one update, A partitioned PSB method for partially separable unconstrained optimization problems, Analysis of sparse quasi-Newton updates with positive definite matrix completion, Solving nonlinear systems of equations by means of quasi-neston methods with a nonmonotone stratgy∗, Optimizing partially separable functions without derivatives, Partitioned quasi-Newton methods for sparse nonlinear equations, Global convergence of the partitioned BFGS algorithm for convex partially separable optimization, A class of diagonal preconditioners for limited memory BFGS method, An implementation of Newton-like methods on nonlinearly constrained networks, On the existence of convex decompositions of partially separable functions, On efficient Hessian computation using the edge pushing algorithm in Julia, Sparse semidefinite programs with guaranteed near-linear time complexity via dualized clique tree conversion, Dynamic scaling based preconditioning for truncated Newton methods in large scale unconstrained optimization, Estimating reducible stochastic differential equations by conversion to a least-squares problem, Recognizing underlying sparsity in optimization, A unified convergence framework for nonmonotone inexact decomposition methods, Solving reachability problems by a scalable constrained optimization method, ve08, Testing a Class of Methods for Solving Minimization Problems with Simple Bounds on the Variables, Optimization of large-scale complex systems, A parallel computing scheme for minimizing a class of large scale functions, Unnamed Item, Local convergence analysis for partitioned quasi-Newton updates, Variable metric methods for unconstrained optimization and nonlinear least squares, Adjoint-based SQP method with block-wise quasi-Newton Jacobian updates for nonlinear optimal control, Quasi-Newton methods for solving underdetermined nonlinear simultaneous equations
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A class of iterative methods for finite element equations
- On modified incomplete cholesky factorization methods for the solution of problems with mixed boundary conditions and problems with discontinuous material conefficients
- On Variable-Metric Methods for Sparse Hessians
- A note about sparsity exploiting quasi-Newton updates
- Variable Metric Method for Minimization
- On the Modification of LDL T Factorizations
- Optimal conditioning of self-scaling variable Metric algorithms
- Quasi-Newton Methods, Motivation and Theory
- Matrix conditioning and nonlinear optimization
- Multi-Level Adaptive Solutions to Boundary-Value Problems
- On Sparse and Symmetric Matrix Updating Subject to a Linear Equation
- Restart procedures for the conjugate gradient method
- Variations on Variable-Metric Methods
