Using Nemirovski's Mirror-Prox method as basic procedure in Chubanov's method for solving homogeneous feasibility problems

We introduce a new variant of Chubanov's method for solving linear homogeneous systems with positive variables. In the Basic Procedure we use a recently introduced cut in combination with Nemirovski's Mirror-Prox method. We show that the cut requires at most (Formula presented.) time, just as Chubanov's cut. In an earlier paper it was shown...

On Some Optimization Problems that Can Be Solved in O(n) Time

We consider nine elementary problems in optimization. We simply explore the conditions for optimality as known from the duality theory for convex optimization. This yields a quite straightforward solution method for each of these problems. The main contribution of this paper is that we show that even in the harder cases the solution needs...

Three-dimensional semi-idealized model for tidal motion in tidal estuaries

In this paper, a three-dimensional semi-idealized model for tidal motion in a tidal estuary of arbitrary shape and bathymetry is presented. This model aims at bridging the gap between idealized and complex models. The vertical profiles of the velocities are obtained analytically in terms of the first-order and the second-order partial...

Infeasible Interior-Point Methods for Linear Optimization Based on Large Neighborhood

In this paper, we design a class of infeasible interior-point methods for linear optimization based on large neighborhood. The algorithm is inspired by a full-Newton step infeasible algorithm with a linear convergence rate in problem dimension that was recently proposed by the second author. Unfortunately, despite its good numerical behavior,...

An Improved and Simplified Full-Newton Step O(n) Infeasible Interior-Point Method for Linear Optimization

We present an improved version of an infeasible interior-point method for linear optimization published in 2006. In the earlier version each iteration consisted of one so-called feasibility step and a few---at most three---centering steps. In this paper each iteration consists of only a feasibility step, whereas the iteration bound improves the...

Kernel-based interior-point methods for monotone linear complementarity problems over symmetric cones

We present an interior-point method for monotone linear complementarity problems over symmetric cones (SCLCP) that is based on barrier functions which are defined by a large class of univariate functions, called eligible kernel functions. This class is fairly general and includes the classical logarithmic function, the self-regular functions, as...

Unified Analysis of Kernel-Based Interior-Point Methods for P?(?)-Linear Complementarity Problems

We present an interior-point method for the P?(?)-linear complementarity problem (LCP) that is based on barrier functions which are defined by a large class of univariate functions called eligible kernel functions. This class is fairly general and includes the classical logarithmic function and the self-regular functions, as well as many non...

Improved Full-Newton Step O(nL) Infeasible Interior-Point Method for Linear Optimization

We present several improvements of the full-Newton step infeasible interior-point method for linear optimization introduced by Roos (SIAM J. Optim. 16(4):1110–1136, 2006). Each main step of the method consists of a feasibility step and several centering steps. We use a more natural feasibility step, which targets the ?+-center of the next pair...

Kernel-function based algorithms for semidefinitie optimization

Recently, Y.Q. Bai, M. El Ghami and C. Roos [3] introduced a new class of so-called eligible kernel functions which are defined by some simple conditions. The authors designed primal-dual interiorpoint methods for linear optimization (LO) based on eligible kernel functions and simplified the analysis of these methods considerably. In this paper...

A new full-Newton step O(n) infeasible interior-point algorithm for semidefinite optimization

Interior-point methods for semidefinite optimization have been studied intensively, due to their polynomial complexity and practical efficiency. Recently, the second author designed a primal-dual infeasible interior-point algorithm with the currently best iteration bound for linear optimization problems. Since the algorithm uses only full Newton...

Generic primal-dual interior point methods based on a new kernel function

In this paper we present a generic primal-dual interior point methods (IPMs) for linear optimization in which the search direction depends on a univariate kernel function which is also used as proximity measure in the analysis of the algorithm. The proposed kernel function does not satisfy all the conditions proposed in

A Class of Large-Update and Small-Update Primal-Dual Interior-Point Algorithms for Linear Optimization

In this paper we present a class of polynomial primal-dual interior-point algorithms for linear optimization based on a new class of kernel functions. This class is fairly general and includes the classical logarithmic function, the prototype self-regular function, and non-self-regular kernel functions as special cases. The analysis of the...

What is on the machine's mind? Models for reasoning with incomplete and uncertain knowledge

In this thesis, which consists of two parts, two different subjects are discussed. In the first part of the thesis a logic for reasoning with inconsistent knowledge will be described. The second part of the thesis contains a proposal for to view a reasoning process as a process of constructing a partial model of the world we are reasoning about....

Report 88-25 (Reviewed) TUD Faculty of Technical Mathematics and Informatics Heuristic reasoning

In this paper a model for heuristic reasoning with uncertain knowledge is presented. This model is a generalisation of the approach proposed by Clancey (Cla-84, Cla-85). We offer a clear semantics for the model, showing that the heuristic reasoning process can be given a clear probabilistic interpretation.

The use of panel methods with a view to problems in aircraft dynamics

A survey is given of the basic principles of the panel methods. The most frequently used methods, steady as well as unsteady, are described in some detail. Recent developments aiming at improvönent and extension of the range of applicability are reviewed. The use of panel methods for the determination of stability derivatives is discussed....

The effect of a pylon-mounted nacelle on the flutter behaviour of a wing-pylon-nacelle configuration