We develop a globally convergent algorithm based on the LP-Newton method which has been recently proposed for solving constrained equations, possibly nonsmooth and possibly with nonisolated solutions. The new algorithm makes use of linesearch for the natural merit function, and preserves the strong local convergence properties of the original LP-Newton scheme. We also present computational expe...

We describe an interior-point algorithm for monotone linear complementarity problems in which primal-dual affine scaling is used to generate the search directions. The algorithm is shown to have global and superlinear convergence with Q-order up to (but not including) two. The technique is shown to be consistent with a potential-reduction algorithm, yielding the first potential-reduction algori...

In this paper, we propose a new version of extragradient method for the variational inequality problem. The method uses a new searching direction which differs from any one in existing projection-type methods, and is of a better stepsize rule. Under a certain generalized monotonicity condition, it is proved to be globally convergent. @ 2001 Eisevier Science Ltd. All rights reserved. Keywords-Vs...

In a recent paper [12], Vishik proved the global wellposedness of the two-dimensional Euler equation in the critical Besov space B 2,1. In the present paper we prove that the Navier-Stokes system is globally well-posed in B 2,1, with uniform estimates on the viscosity. We prove also a global result of inviscid limit. The convergence rate in L is of order ν.

We propose globally convergent iteration schemes for updating the eigenvalues of a symmetric matrix after a rank-1 modiication. Such calculations are the core of the divide-and-conquer technique for the symmetric tridiagonal eigenvalue problem. We prove the superlinear convergence right from the start of our schemes which allows us to improve the complexity bounds of 3]. The eeec-tiveness of ou...

We propose a new numerical method for the computation of the optimal value function of perturbed control systems and associated globally stabilizing optimal feedback controllers. The method is based on a set oriented discretization of state space in combination with a new algorithm for the computation of shortest paths in weighted directed hypergraphs. Using the concept of a multivalued game, w...

The problem of designing a globally exponentially convergent observer for a class of (linear in transport and nonlinear in generation) semi-linear parabolic distributed systems is addressed within a matrix inequality framework, yielding (i) sufficient convergence conditions with physical meaning and (ii) the weight of a Lyapunov functional as design degree of freedom. The proposed approach is i...

This paper is concerned with a Superlinearly feasible SQP algorithm algorithm for general constrained optimization. As compared with the existing SQP methods, it is necessary to solve equality constrained quadratic programming sub-problems at each iteration, which shows that the computational effort of the proposed algorithm is reduced further. Furthermore, under some mild assumptions, the algo...

This paper presents an algorithm for solving multi-stage stochastic nonlinear programs. The algorithm is based on the Lagrangian dual method which relaxes the nonanticipa-tivity constraints, and the barrier function method which enhances the smoothness of the dual objective function so that the Newton search directions can be used. The algorithm is shown to be of globally linear convergence and...

An algorithm for identifying parameters in dynamical systems is developed in this work using homotopy transformations and the single-shooting method. The equations governing the dynamics of the mathematical model are augmented with observer-like homotopy terms that smooth the objective function. As a result, premature convergence to a local minimum is avoided and the obtained parameter estimate...