On the enumeration of self-dual codes

We give the complete classification of all binary, self-dual, doubly-even (32, 16) codes. There are 85 non-equivalent, self-dual, doubly-even (32, 16) codes. Five of these have minimum weight 8, namely, a quadratic residue code and a Reed-Muller code, and three new codes. A set of generators is given for a code in each equivalence class together with its entire weight distribution and the order of its entire group with other information facilitating the computation of permutation generators. From this list it is possible to identify all self-dual codes of length less than 32 and the numbers of these are included.     

Coupled intervals in the discrete calculus of variations: necessity and sufficiency

In this work we study nonnegativity and positivity of a discrete quadratic functional with separately varying endpoints. We introduce a notion of an interval coupled with 0, and hence, extend the notion of conjugate interval to 0 from the case of fixed to variable endpoint(s). We show that the nonnegativity of the discrete quadratic functional is equivalent to each of the following conditions: The nonexistence of intervals coupled with 0, the existence of a solution to Riccati matrix equation and its boundary conditions. Natural strengthening of each of these conditions yields a characterization of the positivity of the discrete quadratic functional. Since the quadratic functional under consideration could be a second variation of a discrete calculus of variations problem with varying endpoints, we apply our results to obtain necessary and sufficient optimality conditions for such problems. This paper generalizes our recent work in [R. Hilscher, V. Zeidan, Comput. Math. Appl., to appear], where the right endpoint is fixed.     

Restricted thresholding: recovering smoothness and preserving edges

Restricted non linear approximation is a generalization of the N‐term approximation in which a measure on the index set of the approximants controls the type, instead of the number, of elements in the approximation. Thresholding is a well‐known type of non linear approximation. We relate a generalized upper and lower Temlyakov property with the decreasing rate of the thresholding approximation. This relation is in the form of a characterization through some general discrete Lorentz spaces. Thus, not only we recover some results in the literature but find new ones. As an application of these results, we compress and reduce noise of some images with wavelets and shearlets and show, at least empirically, that the L²‐norm is not necessarily the best norm to measure the approximation error.     

Predicting initial erosion during the hole erosion test by using turbulent flow CFD simulation

CFD simulation with enhanced modeling of turbulence and near-wall treatment is used to model water–clay mixtures flowing through a cylindrical pipe domain. Effects on the wall-shear stress resulting from varying water clay content and applied hydraulic gradient are analyzed. Various parametric studies were performed and had shown that the two-dimensional modelling introduced in the present study does not yield a uniform wall-shear stress along the pipe wall and that clay concentration affects significantly the wall-shear stress value. This is in contrast with the common hypothesis used in one-dimensional modeling approaches where this stress is assumed constant and which gives rise to uniform erosion along the pipe wall. The obtained results had enabled predicting more realistically erosion amount and had allowed for understanding the irregular eroded hole wall shape as observed experimentally after performing the standard hole erosion test.     

On computing rational Gauss-Chebyshev quadrature formulas

We provide an algorithm to compute the nodes and weights for Gauss-Chebyshev quadrature formulas integrating exactly in spaces of rational functions with arbitrary real poles outside . Contrary to existing rational quadrature formulas, the computational effort is very low, even for extremely high degrees, and under certain conditions on the poles it can be shown that the complexity is of order . This method is based on the derivation of explicit expressions for Chebyshev orthogonal rational functions, which are (thus far) the only examples of explicitly known orthogonal rational functions on with arbitrary real poles outside this interval.

     

Positioning of new brands in an experiment

This paper deals with an experimental investigation of positioning new brands. For this purpose, a management game was carried out with students. The brands introduced in the cause of the game were analysed in respect to their positions in a two-dimensional feature space. We try to find out which of the two strategies, niche policy and imitation, is more frequently used in complex decision situations and if there is a difference in profits. Furthermore, we want to find out, whether differences of prices and advertising exist in our experiment depending on the positioning strategy used.     

Characterization of the Nonemptiness and Compactness of Solution Sets in Convex and Nonconvex Vector Optimization

As a consequence of an abstract theorem proved elsewhere, a vector Weierstrass theorem for the existence of a weakly efficient solution without any convexity assumption is established. By using the notion (recently introduced in an earlier paper) of semistrict quasiconvexity for vector functions and assuming additional structure on the space, new existence results encompassing many results appearing in the literature are derived. Also, when the cone defining the preference relation satisfies some mild assumptions (but including the polyhedral and icecream cones), various characterizations for the nonemptiness and compactness of the weakly efficient solution set to convex vector optimization problems are given. Similar results for a class of nonconvex problems on the real line are established as well.Research supported in part by Conicyt-Chile through FONDECYT 104-0610 and FONDAP-Matemáticas Aplicadas II.     

On coderivatives and Lipschitzian properties of the dual pair in optimization

In this paper, we apply the concept of coderivative and other tools from the generalized differentiation theory for set-valued mappings to study the stability of the feasible sets of both the primal and the dual problem in infinite-dimensional linear optimization with infinitely many explicit constraints and an additional conic constraint. After providing some specific duality results for our dual pair, we study the Lipschitz-like property of both mappings and also give bounds for the associated Lipschitz moduli. The situation for the dual shows much more involved than the case of the primal problem.     

A fast $$(2 + \frac{2}{7})$$ ( 2 + 2 7 ) -approximation algorithm for capacitated cycle covering

Mathematical Programming - We consider the capacitated cycle covering problem: given an undirected, complete graph G with metric edge lengths and demands on the vertices, we want to cover the...     

On the complexity of linear programming under finite precision arithmetic

In this paper we study the complexity of solving linear programs in finite precision arithmetic. This is the normal setup in scientific computation, as digital computers work in finite precision. We analyze two aspects of the complexity: one is the number of arithmetic operations required to solve the problem approximately, and the other is the working precision required to carry out some critical computations safely. We show how the conditioning of the problem instance affects the working precision required and the computational requirements of a classical logarithmic barrier algorithm to approximate the optimal value of the problem within a given tolerance. Our results show that these complexity measures depend linearly on the logarithm of a certain condition measure. We carry out the analysis by looking at how well Newton's Method can follow the central trajectory of the feasible set, and computing error bounds in terms of the condition measure. These results can be interpreted as a theoretical indication of good numerical behavior of the logarithmic barrier method, in the sense that a problem instance twice as hard as the other from the numerical point of view, requires only at most twice as much precision to be solved. © 1998 The Mathematical Programming Society, Inc. Published by Elsevier Science B.V.This research has been supported through grants from Fundación Andes, under agreement C12021/7, and FONDECYT (project number 1930948).