New developments in the primal-dual column generation technique

The classical column generation is based on optimal solutions of the restricted master problems. This strategy frequently results in an unstable behaviour and may require an unnecessarily large number of iterations. To overcome this weakness, variations of the classical approach use interior points of the dual feasible set, instead of optimal solutions. In this paper, … Read more

Energy Savings in Wireless Mesh Networks in a Time-Variable Context

Energy consumption of communication systems is becoming a fundamental issue and, among all the sectors, wireless access networks are largely responsible for the in- crease in consumption. In addition to the access segment, wireless technologies are also gaining popularity for the back- haul infrastructure of cellular systems mainly due to their cost and easy deployment. … Read more

Epigraphical cones I

Up to orthogonal transformation, a solid closed convex cone $K$ in the Euclidean space $\mathbb{R}^{n+1}$ is the epigraph of a nonnegative sublinear function $f:\mathbb{R}^n\to \mathbb{R}$. This work explores the link between the geometric properties of $K$ and the analytic properties of $f$. CitationJOURNAL OF CONVEX ANALYSIS, 2011, in press. ArticleDownload View PDF

Epigraphical cones II

This is the second part of a work devoted to the theory of epigraphical cones and their applications. A convex cone $K$ in the Euclidean space $\mathbb{R}^{n+1}$ is an epigraphical cone if it can be represented as epigraph of a nonnegative sublinear function $f: \mathbb{R}^n\to \mathbb{R}$. We explore the link between the geometric properties of … Read more

Error bounds for vector-valued functions: necessary and sufficient conditions

In this paper, we attempt to extend the definition and existing local error bound criteria to vector-valued functions, or more generally, to functions taking values in a normed linear space. Some new derivative-like objects (slopes and subdifferentials) are introduced and a general classification scheme of error bound criteria is presented. CitationPublished in Nonlinear Analysis. Theory, … Read more

The iBP algorithm for the discretizable molecular distance geometry problem with interval data

The Distance Geometry Problem in three dimensions consists in finding an embedding in R^3 of a given nonnegatively weighted simple undirected graph such that edge weights are equal to the corresponding Euclidean distances in the embedding. This is a continuous search problem that can be discretized under some assumptions on the minimum degree of the … Read more

A Bound for the Number of Different Basic Solutions Generated by the Simplex Method

In this short paper, we give an upper bound for the number of different basic feasible solutions generated by the simplex method for linear programming problems having optimal solutions. The bound is polynomial of the number of constraints, the number of variables, and the ratio between the minimum and the maximum values of all the … Read more

Multiobjective DC Programming with Infinite Convex Constraints

In this paper new results are established in multiobjective DC programming with infinite convex constraints ($MOPIC$ for abbr.) that are defined on Banach space (finite or infinite) with objectives given as the difference of convex functions subject to infinite convex constraints. This problem can also be called multiobjective DC semi-infinite and infinite programming, where decision … Read more

Some Properties of Convex Hulls of Integer Points Contained in General Convex Sets

In this paper, we study properties of general closed convex sets that determine the closed-ness and polyhedrality of the convex hull of integer points contained in it. We first present necessary and sufficient conditions for the convex hull of integer points contained in a general convex set to be closed. This leads to useful results … Read more

Piecewise quadratic approximations in convex numerical optimization

We present a bundle method for convex nondifferentiable minimization where the model is a piecewise quadratic convex approximation of the objective function. Unlike standard bundle approaches, the model only needs to support the objective function from below at a properly chosen (small) subset of points, as opposed to everywhere. We provide the convergence analysis for … Read more