167 research outputs found
Adaptive matrix algebras in unconstrained minimization
In this paper we study adaptive L(k)QNmethods, involving special matrix algebras of low complexity, to solve general (non-structured) unconstrained minimization problems. These methods, which generalize the classical BFGS method, are based on an iterative formula which exploits, at each step, an ad hocchosen matrix algebra L(k). A global convergence result is obtained under suitable assumptions on f
Low complexity secant quasi-Newton minimization algorithms for nonconvex functions
In this work some interesting relations between results on basic optimization and algorithms for nonconvex functions (such as BFGS and secant methods) are pointed out. In particular, some innovative tools for improving our recent secant BFGS-type and LQN algorithms are described in detail
Truncated Nonsmooth Newton Multigrid for phase-field brittle-fracture problems
We propose the Truncated Nonsmooth Newton Multigrid Method (TNNMG) as a
solver for the spatial problems of the small-strain brittle-fracture
phase-field equations. TNNMG is a nonsmooth multigrid method that can solve
biconvex, block-separably nonsmooth minimization problems in roughly the time
of solving one linear system of equations. It exploits the variational
structure inherent in the problem, and handles the pointwise irreversibility
constraint on the damage variable directly, without penalization or the
introduction of a local history field. Memory consumption is significantly
lower compared to approaches based on direct solvers. In the paper we introduce
the method and show how it can be applied to several established models of
phase-field brittle fracture. We then prove convergence of the solver to a
solution of the nonsmooth Euler-Lagrange equations of the spatial problem for
any load and initial iterate. Numerical comparisons to an operator-splitting
algorithm show a speed increase of more than one order of magnitude, without
loss of robustness
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