This paper concerns the random fluctuation theory of a one dimensional elliptic equation with highly oscillatory random coefficient. Theoretical studies show that the rescaled random corrector converges in distribution to a stochastic integral with respect to Brownian motion when the random coefficient has short-range correlation. When the random coefficient has long range correlation, it was s...

In the present paper we present a methodology that is applicable to large-eddy simulations of fluid structure interaction problems. The fluid flow equations are solved on a fixed grid that does not conform to the structure, and boundary conditions are imposed using a local reconstruction procedure. The structure that undergoes both linear-elastic and large-angle/large-displacement rigid body mo...

A grid model was developed to combine small-scale grid resolution and long-term predictions of radionuclide dispersion in shallow seas. A predictor-corrector algorithm ensures an unconditional stability of the model. Four modules calculate the concentration of suspended sediments, the dispersion of radionuclides in the marine environment, and the doses to members of the public and marine biota....

In this paper we present a variant of Vavasis and Ye’s layered-step path following primaldual interior-point algorithm for linear programming. Our algorithm is a predictor-corrector type algorithm which uses from time to time the least layered squares (LLS) direction in place of the affine scaling direction. It has the same iteration-complexity bound of Vavasis and Ye’s algorithm, namely O(n3.5...

Motivated by a numerical example which shows that a feasible version of Mehrotra’s original predictor-corrector algorithm might be inefficient in practice, Salahi et al., proposed a so-called safeguard based variant of the algorithm that enjoys polynomial iteration complexity while its practical efficiency is preserved. In this paper we analyze the same Mehrotra’s algorithm from a different per...

We introduce a new class of numerical schemes for the solution of the Cauchy problem for non-stiff ordinary differential equations (ODEs). Our algorithms are of the predictor-corrector type; they are obtained via the decomposition of the solutions of the ODEs into combinations of appropriately chosen exponentials, whereas the classical schemes are based on the approximation of solutions by poly...

The paper provides a detailed analysis of a short step interior point algorithm applied to linear control constrained optimal control problems. Using an affine invariant local norm and an inexact Newton corrector, the well-known convergence results from finite dimensional linear programming can be extended to the infinite dimensional setting of optimal control. The present work complements a re...

In this paper, a monotone linear complementarity reformulation of the nonnegative least squares problems in inequality sense is introduced. Then Mehrotra’s predictor-corrector interior point algorithm is applied to solve the resulting monotone linear complementarity problem. Our numerical experiments on several randomly generated test problems show that Mehrotra’s algorithm overperforms the wid...

A higher order corrector-predictor interior-point method is proposed for solving sufficient linear complementarity problems. The algorithm produces a sequence of iterates in the N− ∞ neighborhood of the central path. The algorithm does not depend on the handicap κ of the problem. It has O((1 + κ) √ nL) iteration complexity and is superlinearly convergent even for degenerate problems.