BLANCO IZQUIERDO , Víctor

Esta tesis doctoral estudia algunos de los aspectos algebraicos de la optimización multiobjetivo lineal y polinomial. Primeramente, en el Capítulo 1 se introducen los conceptos básicos necesarios para el desarrollo de los métodos presentados: la presentación del problema multiobjetivo, y el concepto de solución no dominada (o Pareto óptima);...

In this paper, we propose an extension of the uncapacitated hub location problem where the potential posi-tions of the hubs are not fixed in advance. Instead, they are allowed to belong to a region around an initialdiscrete set of nodes. We give a general framework in which the collection, transportation, and distributioncosts are based on...

This paper presents a new methodology for solving multiobjective integer linear programs (MOILP) using tools from algebraic geometry. We introduce the concept of partial Gr¨obner basis for a family of multiobjective programs where the right-hand side varies. This new structure extends the notion of Gr¨obner basis for the single objective case...

This paper addresses the problem of decomposing a numerical semigroup into mirreducible numerical semigroups. The problem originally stated in algebraic terms is translated, introducing the so-called Kunz-coordinates, to resolve a series of several discrete optimization problems. First, we prove that finding a minimal m-irreducible...

This paper studies Minimum Spanning Trees under incomplete information for its vertices. We assume that no information is available on the precise placement of vertices so that it is only known that vertices belong to some neighborhoods that are second order cone representable and distances are measured with a ℓq-norm. Two mixed integer non...

In this paper, we present a novel approach to construct multiclass classifiers by means of arrangements of hyperplanes. We propose different mixed integer (linear and non linear) programming formulations for the problem using extensions of widely used measures for misclassifying observations where the kernel trick can be adapted to be...

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In this paper we propose a novel methodology to construct Optimal Classification Trees that takes into account that noisy labels may occur in the training sample. The motivation of this new methodology is based on the superaditive effect of combining together margin based classifiers and outlier detection techniques. Our approach rests on two...

This paper addresses the general continuous single facility location problems in finite dimension spaces under possibly different ℓp norms in the demand points. We analyze the difficulty of this family of problems and revisit convergence properties of some well-known algorithms. The ultimate goal is to provide a common approach to solve the...

In this paper we propose a general methodology for solving a broad class of continuous, multifacility location problems, in any dimension and with ℓτ -norms proposing two different methodologies: 1) by a new second order cone mixed integer programming formulation and 2) by formulating a sequence of semidefinite programs that converges to the...

Several algorithms are available in the literature for finding the entire set of Pareto-optimal solutions in MultiObjective Linear Programming (MOLP). However, it has not been proposed so far an interior point algorithm that finds all Pareto-optimal solutions of MOLP. We present an explicit construction, based on a transformation of any MOLP...