Lines Matching refs:method
88 minimization method (e.g., limited-memory variable metric, conjugate
133 discussed in the following sections. The solution method should be
141 a TAO method will override any method specified by the second argument.
143 specify the limited-memory quasi-Newton line search method for
171 method also implements its own specialized options. Please refer to the
412 matrix-free method. The matrix-free variant is allowed *only* when the
413 linear systems are solved by an iterative method in combination with no
638 This method is set by using the linearly constrained augmented
723 method, but faster results may be obtained by manipulating the structure
858 1. Function evaluation only – Nelder-Mead method (`tao_nm`)
860 method (`tao_lmvm`) and nonlinear conjugate gradient method
866 The best method to use depends on the particular problem being solved
871 method is likely to perform best. The Nelder-Mead method should be used
888 The Newton line search method solves the symmetric system of equations
914 The Newton line search method can be selected by using the TAO solver
1103 conjugate gradient method, Nash conjugate gradient method,
1104 Steihaug-Toint conjugate gradient method, generalized Lanczos method, or
1105 an alternative Krylov subspace method supplied by PETSc. The method used
1113 generalized Lanczos method, this preconditioner must be symmetric and
1125 the Krylov subspace method is not a descent direction, the Krylov method
1130 The perturbation is decreased as long as the Krylov subspace method
1136 direction or the Krylov subspace method, the perturbation is
1148 the `gltr` method to solve the system of equations, an estimate of
1155 the direction or Krylov subspace method, the perturbation is
1169 either the direction or Krylov subspace method, the perturbation is
1193 method. The method for initializing the trust-region radius is set with
1203 algorithm. The `constant` method initializes the trust-region radius
1207 standard conjugate gradient method and initializes the trust region to
1210 The method for updating the trust-region radius is set with the command
1212 `step` is the default. The `step` method updates the trust-region
1229 `reduction` method computes the ratio of the actual reduction in the
1249 `interpolation` method uses the same interpolation mechanism as in the
1258 The Newton trust-region method solves the constrained quadratic
1277 trust-region method can be set by using the TAO solver `tao_ntr`. The
1298 > | | interpolation | | method |
1336 > | | reduction, | | update method |
1449 Lanczos method to the symmetric system of equations
1450 $H_k d = -g_k$. The method used to solve the system of equations
1458 gradient methods and generalized Lanczos method, this preconditioner
1468 The method for computing an initial trust-region radius is set with the
1478 algorithm. The `constant` method initializes the trust-region radius
1482 standard conjugate gradient method and initializes the trust region to
1485 The method for updating the trust-region radius is set with the command
1487 `reduction` is the default. The `reduction` method computes the
1507 `interpolation` method uses the same interpolation mechanism as in the
1529 The limited-memory, variable-metric method (LMVM) computes a positive definite
1550 process is repeated until the method converges. This algorithm is the
1586 The nonlinear conjugate gradient method can be viewed as an extension of
1587 the conjugate gradient method for solving symmetric, positive-definite
1591 conjugate gradient method can be selected by using the TAO solver
1596 Fletcher-Reeves method, the Polak-Ribiére method, the Polak-Ribiére-Plus
1597 method {cite}`nocedal2006numerical`, the Hestenes-Stiefel method, and the
1598 Dai-Yuan method. These conjugate gradient methods can be specified by
1602 The conjugate gradient method incorporates automatic restarts when
1619 direct search method for finding a local minimum of a function
1750 method. Trust-region conjugate gradient methods (`KSPNASH`,
1793 trust-region conjugate gradient method is used for the Hessian
1801 BNTR globalizes the Newton step using a trust region method based on the
1826 solution, and therefore the quasi-Newton method chosen must guarantee a
1879 $0.5$ respectively. The Kou-Dai method has multiple parameters.
1889 `-tao_bncg_neg_xi`. Finally, the Broyden method has its convex
1891 by default, i.e. it is by default the BFGS method. One can also
1898 depending on the method from initial testing.
1900 BNCG also offers a special type of method scaling. It employs Broyden
1906 method being used. For example, in our preliminary computations, the
1907 forward formulation works better for the SSML_BFGS method, but the
1908 inverse formulation works better for the Hestenes-Stiefel method. The
1923 The active set estimation uses the Bertsekas-based method described in
1928 tolerance and estimator step length used in the Bertsekas method can be
1959 of dual ascent with the superior convergence properties of the method of
1974 $f(x)$, and one for $g(z)$. With method of multipliers, one
2020 The TAOALMM method solves generally constrained problems of the form
2064 trust-region method (TAOBQNKTR). Other first-order methods such as
2070 The TAOPDIPM method (`-tao_type pdipm`) implements a primal-dual interior
2071 point method for solving general nonlinear programming problems of the form
2128 method using PETSc’s SNES object. After each Newton iteration, a
2154 This method is set by using the linearly constrained augmented
2167 constrained augmented Lagrangian method approximately solves the
2285 We apply one step of a limited-memory quasi-Newton method to this
2388 The TAOBRGN algorithms is a Gauss-Newton method is used to iteratively solve nonlinear least
2398 words, the Gauss-Newton method approximates the Hessian of the objective
2474 ({eq}`eq_poundersp`) with the BLMVM method described in
2680 function {cite}`fischer:special`. A nonsmooth Newton method
2726 by applying a nonsmooth Newton method with a line search. We calculate a
2742 termed an infeasible semismooth method. This method can be specified by
2757 a projected Armijo line search. This method can be specified by using
2766 The recommended algorithm is the infeasible semismooth method,
2782 termed an infeasible active-set semismooth method. This method can be
2786 a projected Armijo line search. This method can be specified by using
2819 The BQPIP algorithm is an interior-point method for bound constrained
2823 gradient, and Hessian only once. This method also requires the solution
2854 The TRON {cite}`lin_c3` algorithm is an active-set method
2856 conjugate gradient method to minimize an objective function. Each
2861 applies a preconditioned conjugate gradient method to a quadratic model
2882 BLMVM is a limited-memory, variable-metric method and is the
2883 bound-constrained variant of the LMVM method for unconstrained
2885 eliminating the need for Hessian evaluations. The method can be set by
3055 5. PETSc provides the user a convenient method for setting options at
3110 gradient method.
3295 created by earlier routines. For the nonlinear conjugate gradient method