Alfredo García Hernández-Díaz

Pablo de Olavide University | UPO · Department of Economy, Cuantitative Methods and Economic History

The aim of this research was to assess the learning efficacy and level of satisfaction of university students as they adapted to the online teaching model amid the restrictions imposed as a result of COVID-19. The sample consisted of 467 students attending a public University of Spain. The study applied a structural equations methodology with a tri...

El uso de Internet y el desarrollo de las nuevas tecnologías han provocado importantes cambios en la enseñanza y en el aprendizaje de los estudiantes de educación superior. La pandemia provocada por la Covid-19 ha hecho que muchas universidades hayan tenido que transferir sus actividades presenciales a la docencia online. Por este motivo, el objeti...

This paper presents a competitive algorithm that combines the Greedy Randomized Adaptive Search Procedure including a Tabu Search instead of a traditional Local Search framework, with a Strategic Oscillation post-processing, to provide high-quality solutions for the α-neighbor p-center problem (α−pCP). This problem seeks to locate p facilities to s...

This paper presents a hybridization of Strategic Oscillation with Path Relinking to provide a set of high-quality nondominated solutions for the Multiobjective k-Balanced Center Location problem. The considered location problem seeks to locate k out of m facilities in order to serve n demand points, minimizing the maximum distance between any deman...

The use of the Internet to develop new technologies has generated a considerable change in teaching and student learning in higher education. The pandemic caused by COVID-19 has forced universities to switch from face-to-face to online instruction. Furthermore, this transfer process was planned and executed quickly, with urgent redesigns of courses...

In this paper, a new solution method is implemented to solve a bi‐objective variant of the vehicle routing problem that appears in industry and environmental enterprises. The solution involves designing a set of routes for each day in a period, in which the service frequency is a decision variable. The proposed algorithm, a muti‐start multi‐objecti...

A Muti-Start Multiobjective Local Search algorithm is implemented to solve a bi-objective variant of the Vehicle Routing Problem appearing in industry and environmental enterprises. The problem seeks to design a set of routes for each time on a period and in which the service frequency is a decision variable. The algorithm minimizes total emissions...

This paper presents two metaheuristic algorithms for the solution of the p-next center problem: a Greedy Randomized Adaptive Search Procedure and a Variable Neighborhood Search algorithm, that will be subsequently hybridized. The p-next center problem is a variation of the p-center problem, which consists of locating p out of n centers and assignin...

In this paper, the MinMax‐COVRP (where COVRP is capacitated open vehicle routing problem) is considered as a variation of the COVRP where the objective is to minimize the duration of the longest route. For the purpose of producing high‐quality solutions, elements from the fields of mathematical programming and metaheuristics are combined, resulting...

In this paper, a problem based on real-world situations in humanitarian logistics is considered, where the main characteristics are the lack of available vehicles and the imperative need of a quick evacuation of all the affected by a disaster, but within the minimum possible travel cost. These aspects will be considered within a Multi-objective Cap...

In this paper, the waste collection problem (WCP) of a city in the south of Spain is addressed as a multiobjective routing problem that considers three objectives. From the company's perspective, the minimization of the travel cost is desired as well as that of the total number of vehicles. Additionally, from the employee's point of view, a set of...

In this paper, the Waste Collection Problem of a city in the south of Spain is addressed as a multi-objective routing problem that considers three objectives. From the company’s perspective, the minimization of the travel cost is desired as well as that of the total number of vehicles. Additionally, from the employee’s point of view, a set of balan...

In recent years, many public bike rental systems have proliferated in Spain. Unfortunately, many have had to close because of their poor financial feasibility. The aim of this paper is twofold. On the one hand, a benchmarking of the main public bicycle systems in Spain is conducted, analysing the growth in the last decades, with special emphasis on...

The aim of this paper is to propose a framework in order to solve the real-world Waste Collection Problem in a city of southern Spain modeled as an Asymmetric Vehicle Routing Problem (AVRP) with side constraints and several variations. In this problem, not only vehicle capacity and temporal constraints are considered but multiple trips are also all...

Differential Evolution is an efficient metaheuristic for continuous optimization that suffers from the curse of dimensionality. A large amount of experimentation has allowed researchers to find several potential weaknesses in Differential Evolution. Some of these weaknesses do not significantly affect its performance when dealing with low-dimension...

While the cross entropy methodology has been applied to a fair number of combinatorial optimization problems with a single objective, its adaptation to multiobjective optimization has been sporadic. We develop a multiobjective optimization cross entropy (MOCE) procedure for combinatorial optimization problems for which there is a linear relaxation...

The aim of this paper is to solve a real-world problem proposed by an international company operating in Spain and modeled as a variant of the Open Vehicle Routing Problem in which the makespan, i.e., the maximum time spent on the vehicle by one person, must be minimized. A competitive multi-start algorithm, able to obtain high quality solutions wi...

En el presente trabajo mostramos los resultados más relevantes obtenidos en un proceso de encuestación a 300 usuarios de la estación "Pablo de Olavide" del metro de Sevilla. El objetivo del trabajo es doble: por un lado, analizar el perfil del usuario (motivaciones por las que usan el metro, intermodalidad y flujos); mientras que, por otro lado, a...

In this paper the most relevant results obtained in a survey conducted by 300 users of the "Pablo de Olavide" Seville metro stop are presented. The aim of the paper is twofold. On the one hand, the user profile is analysed: motivations for using the subway, intermodality and ows, whereas, on the other hand, the price elasticity of demand is partial...

Multi-criteria optimization problems are considered where the decision maker is unable to determine the exact weights of importance of the criteria but can provide some imprecise information about these weights. Two solution concepts are studied in this framework: the optimistic min–max solution and the compromise utilitarian solution, both of whic...

Single objective optimization algorithms are the basis of the more complex optimization algorithms such as multi-objective optimizations algorithms, niching algorithms, constrained optimization algorithms and so on. Research on the single objective optimization algorithms influence the development of these optimization branches mentioned above. In...

Vehicle Routing Problems (VRP) arise in transportation problems optimizing one or several objectives in conflict. We will focus on Open Vehicle Routing Problems with a homogeneous fleet and three objectives (total distance, maximum travel time and number of routes). We propose a multiobjective local search based algorithm capable of obtaining effic...

RESUMEN Durante el presente curso 2009/2010 la Universidad Pablo de Olavide (UPO), de Sevilla, ha puesto en marcha el nuevo mapa de titulaciones adaptado al Espacio Europeo de Educación Superior (EEES), el cual está compuesto por 16 grados y 6 dobles grados. Hasta llegar a este punto la UPO trabajó duro durante más de 6 años en la adaptación de su...

1 Abstract In this paper, we deal with the problem of handling solutions in an external archive with the use of a relaxed form of Pareto dominance called -dominance and a variation of it called pa-dominance. These two relaxed forms of Pareto dominance have been used as archiving strategies in some multi-objective evolutionary algorithms (MOEAs). Th...

There is renewed interest in the development of effective and efficient methods for optimizing models of which the optimizer has no structural knowledge. This is what in the literature is referred to as optimization of black boxes. In particular, we address the challenge of optimizing expensive black boxes, that is, those that require a significant...

In the field of single-objective optimization, hybrid variants of gradient based methods and evolutionary algorithms have been shown to performance better than the pure evolutionary method. This same idea has been used with Evolutionary Multiobjective Optimization (EMO), obtaining also very promising results. In most of the cases, gradient informat...

Any organization is routinely faced with the need to make decisions regarding the selection and scheduling of project portfolios from a set of candidate projects. We propose a multiobjective binary programming model that facilitates both obtaining efficient portfolios in line with the set of objectives pursued by the organization, as well as their...

The aim of this paper is to show how the hybridization of a multi-objective evolutionary algorithm (MOEA) and a local search method based on the use of rough set theory is a viable alternative to obtain a robust algorithm able to solve difficult constrained multi-objective optimization problems at a moderate computational cost. This paper extends a...

One of the main tools for including decision maker (DM) preferences in the multiobjective optimization (MO) literature is the use of reference points and achievement scalarizing functions [A.P. Wierzbicki, The use of reference objectives in multiobjective optimization, in: G. Fandel, T. Gal (Eds.), Multiple-Criteria Decision Making Theory and Appli...

Because of the conflicting nature of criteria or objectives, solving a multiobjective optimization problem typically requires interaction with a decision maker who can specify preference information related to the objectives in the problem in question. Due to the difficulties of dealing with multiple objectives, the way information is presented pla...

This paper studies a Geo/G/1/∞ queueing system under an (m,N)-policy, i.e., the service station operates under an N-policy with an early setup where the startup period begins when m(≤N) customers accumulate in the system. Moreover, it is assumed that the i-th service of each customer is either unsuccessful (and then the customer joins the server fo...

This paper presents a new algorithm that approximates real function evaluations using supervised learning with a surrogate method called support vector machine (SVM). We perform a comparative study among different leader selection schemes in a multi-objective particle swarm optimizer (MOPSO), in order to determine the most appropriate approach to b...

Recent works have shown how hybrid variants of gradient-based methods and evolutionary algorithms perform better than a pure evolutionary method both for single-objective and multiobjective optimization. This same idea has been used with Evolutionary Multiobjective Optimization (EMO), obtaining also very promising results. In most cases, gradient i...

In this chapter, we propose the use of rough sets to improve the approximation provided by a multi-objective evolutionary algorithm. The main idea is to use this sort of hybrid approach to approximate the Pareto front of a multi-objective optimization problem with a low computational cost (only 3000 fitness function evaluations). The hybrid operate...

This paper presents an approach in which a multi-objective evolutionary algorithm (MOEA) is coupled to a surrogate method in order to explore the search space in an efficient manner. A small comparative study among three surrogate methods is conducted: an artificial neural network (ANN), a radial basis function (RBF) and a support vector machine (S...

In the field of single-objective optimization, hybrid variants of gradient-based methods and evolutionary algorithms have been shown to perform better than an evolutionary method by itself. This same idea has been recently used in Evolutionary Multiobjective Optimization (EMO), obtaining also very promising results. In most cases, gradient informat...

In this paper, we propose the combination of different optimization techniques in order to solve "hard" two- and three-objective optimization problems at a relatively low computational cost. First, we use the ε-constraint method in order to obtain a few points over (or very near of) the true Pareto front, and then we use an approach based on rough...

The transition to a hydrogen economy requires appropriate regional planning to take advantage of the each region potential. This paper deals with a first phase of this process, which consists of satisfying around 10% of the energy demand for transport in Spain by 2010 through renewable energy sources. Planning has been carried out via a multiobject...

This work applies the non-parametric technique of Data Envelopment Analysis (DEA) to conduct a multicriteria comparison of some existing and under development technologies in the automotive sector. The results indicate that some of the technologies under development, such as hydrogen fuel cell vehicles, can be classified as efficient when evaluated...

This paper presents a new multi-objective evolutionary algorithm (MOEA) which adopts a radial basis function (RBF) approach in order to reduce the number of fitness function evaluations performed to reach the Pareto front. The specific method adopted is derived from a comparative study conducted among several RBFs. In all cases, the NSGA-II (which...

Efficiency has become one of the main concerns in evolutionary multiobjective optimization during recent years. One of the possible alternatives to achieve a faster convergence is to use a relaxed form of Pareto dominance that allows us to regulate the granularity of the approximation of the Pareto front that we wish to achieve. One such relaxed fo...

Las organizaciones se enfrentan fundamentalmente al problema de cómo invertir sus recursos escasos entre un conjunto de alternativas o proyectos candidatos. Para ayudar a dar respuesta a este problema presentamos el siguiente estudio en el que lo que se persigue es seleccionar, en función de un conjunto de criterios y recursos existentes, una carte...

En el presente trabajo mostramos cómo el uso combinado de las buenas propiedades mostradas hasta ahora tanto por los métodos exactos de optimización, principalmente los basados en el uso del gradiente de las funciones objetivo, como por los algoritmos metaheurísticos dan lugar a algoritmos híbridos capaces de resolver problemas de optimización mult...

The lack of sustainability of the current Spanish energy system makes it necessary to study the adoption of alternative energy models. One of these is what is known as the hydrogen economy. In this paper, we aim to plan, for the case of Spain, an initial phase for transition to this energy model making use of the potential offered by each Spanish r...

This paper presents a new multi-objective evolutionary al- gorithm (MOEA) based on differential evolution and rough sets theory. The proposed approach adopts an external archive in order to retain the nondominated solutions found during the evolutionary process. Additionally, the approach also incorporates the concept of pa� -dominance to get a goo...

La distribución de espacios es un problema que habitualmente se presenta en situaciones reales cuando se deben asignar simultáneamente diferentes conjuntos de espacios (despachos, habitaciones, salas, etc.) distribuidos entre edificios y/o plantas entre varios grupos de personas de tal forma que se minimicen las distancias entre los espacios asigna...

This paper presents a new multi-objective evolutionary algorithm which consists of a hybrid between a particle swarm optimization approach and some concepts from rough sets theory. The main idea of the approach is to combine the high convergence rate of the particle swarm optimization algorithm with a local search approach based on rough sets that...

This paper analyzes a discrete-time single-server queue under bilevel threshold control and early setup. The joint generating function of the server state and the number of customers in the system together with the main performance measures are derived. We also study the length of the different busy periods of the server as well as the number of cu...

El Espacio Europeo de Educación Superior (EEES) se presenta como el principal reto de los últimos años al que debe enfrentarse la Universidad española. La puesta en marcha de este nuevo marco de acción supone un replanteamiento general de todo lo que se refiere, por un lado, a la estructura de las materias que conformarán las futuras titulaciones y...

La Revista de Métodos Cuantitativos para la Economía y la Empresa pretende ser un medio de comunicación útil para todos los que investigan en técnicas Matemáticas, Estadísticas o Econométricas y sus posibles aplicaciones al ámbito económico o empresarial. La edita un grupo de profesores del Departamento de Economía, Métodos Cuantitativos e Historia...

The distribution of spaces is a usual real problem presented when we have to assign simultaneously different sets of spaces (offices, rooms, halls, etc.). These spaces are distributed in buildings and/or floors and have to be assigned among several groups of people. The aim is to minimize the total distance among the spaces assigned to each group a...

El objetivo de este trabajo es analizar la clasificación de universidades públicas españolas presentada por el periódico El Mundo (2004) para el período 2002-2003. Para ello aplicaremos una serie de técnicas de clasificación a los datos de universidades públicas españolas de ese mismo período proporcionados por el estudio Hernández (2004). Los proc...

Let $\varphi $ and $\psi $ be two analytic functions defined on ${\bbb D}$ such that $\varphi ( {\bbb D}) \subseteq {\bbb D}$. The operator given by $f\mapsto \psi ( f\circ \varphi ) $ is called a weighted composition operator. For each $1\leq p\leq \infty ,$ let $S_{p}$ be the space of analytic functions on ${\bbb D}$ whose derivatives belong to t...

Let j \varphi and y \psi be two analytic functions defined on \mathbbD \mathbb{D} such that j(\mathbbD) Í \mathbbD \varphi(\mathbb{D}) \subseteq\mathbb{D} . The operator given by f®y(f°j) f\mapsto\psi(f\circ\varphi) is called a weighted composition operator. In this paper we deal with the boundedness, compactness, weak compactness, and complete...

Let ϕ, ψ be analytic functions defined on , such that ϕ() ⊆ . The operator given by f ↦ ψ(f ∘ ϕ) is called a weighted composition operator. In this paper we deal with the boundedness, compactness, weak compactness, and complete continuity of weighted composition operators on Hardy spaces Hp (1 ≤ p < ∞). In particular, we prove that such an operator...

We characterize the boundedness and compactness of weighted composition operators between weighted Banach spaces of analytic functions H_v^0 and H_vînfty. we estimate the essential norm of a weighted composition operator and compute it for those Banach spaces H_v^0 which are isomorphic to c0. We also show that, when such an operator is not compact,...