49M15 Newton-type methods
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A continuity result for Nemyckii Operators and some applications in PDE constrained optimal control
(2006)
This work explores two applications of a classical result on the continuity of Nemyckii operators to optimal control with PDEs. First, we present an alternative approach to the analysis of Newton's method for function space problems involving semi-smooth Nemyckii operators. A concise proof for superlinear convergence is presented, and sharpened bounds on the rate of convergence are derived. Second, we derive second order sufficient conditions for problems, where the underlying PDE has poor regularity properties. We point out that the analytical structure in both topics is essentially the same.
A thorough convergence analysis of the Control Reduced Interior Point Method in function space is performed. This recently proposed method is a primal interior point pathfollowing scheme with the special feature, that the control variable is eliminated from the optimality system. Apart from global linear convergence we show, that this method converges locally almost quadratically, if the optimal solution satisfies a function space analogue to a non-degeneracy condition. In numerical experiments we observe, that a prototype implementation of our method behaves in compliance with our theoretical results.
A path following algorithm for linear complementarity problems is presented. Given a point $z$ that approximates a point $z(\tau)$ on the central path with complementarity gap $\tau$, one determines a parameter $\theta\in (0,1)$ so that this point satisfies the hypothesis of the affine invariant Kantorovich Theorem for the equation defining $z((1-\theta)\tau)$. It is shown that $\theta$ is bounded below by a multiple of $n^{-1/2}$, where $n$ is the dimension of the problem. Since the hypothesis of of the Kantorovich Theorem is satisfied the sequence generated by Newton's method, or by the simplified Newton method, will converge to $z((1-\theta)\tau)$. We show that the number of steps required to obtain an acceptable approximation of $z((1-\theta)\tau)$ is bounded above by a number independent of $n$. Therefore the algorithm has $O(\sqrt{n}L)$-iteration complexity. The parameters of the algorithm can be determined in such a way that only one Newton step is needed each time the complementarity gap is decreased.
A wide range of free boundary problems occurring in engineering andindustry can be rewritten as a minimization problem for astrictly convex, piecewise smooth but non--differentiable energy functional.The fast solution of related discretized problemsis a very delicate question, because usual Newton techniquescannot be applied. We propose a new approach based on convex minimization and constrained Newton type linearization. While convex minimization provides global convergence of the overall iteration, the subsequent constrained Newton type linearization is intended to accelerate the convergence speed. We present a general convergence theory and discuss several applications.