Modelos de localización continua

En este trabajo se revisan tres modelos de problemas de localización continua: (1) un problema general de localización con respecto a regiones de demanda; (2) el problema de la mediana ordenada y (3) un problema de localización multiobjetivo. Con ellos se pretende dar una amplia muestra de los problemas que aparecen en el ámbito de la Teoría de Localización continua, así como estudiar propiedades que permitan caracterizar los conjuntos de soluciones. El trabajo incluye una larga lista de referencias que facilitarán al lector adentrarse más profundamente en éstos y otros modelos de la Teoría de Localización.Ministerio de Ciencia y Tecnologí

Robust positioning of service units

In this paper, we address the problem of locating mobile service units to cover random incidents. The model does not assume complete knowledge of the probability distribution of the location of the incident to be covered. Instead, only the mean value of that distribution is known. We propose the minimization of the maximum expected response time as an effectiveness measure for the model. Thus, the solution obtained is robust with respect to any probability distribution. The cases of one and two service units under the nearest allocation rule are studied in the paper. For both problems, the optimal solutions are shown to be degenerate distributions for the servers

On the exponential cardinality of FDS for the ordered p-median problem

We study finite dominating sets (FDS) for the ordered median problem. This kind of problems allows to deal simultaneously with a large number of models. We show that there is no valid polynomial size FDS for the general multifacility version of this problem even on path networks

Improved heuristics for solving large-scale Scanning Transmission Electron Microscopy image segmentation using the ordered median problem

The discrete ordered median problem can be applied in a wide variety of areas. The application of this problem in electron tomography image segmentation is currently being considered since high-quality images are obtained when this model is applied. However, its application means that a high computing time is required to obtain solutions for large-scale instances. The size of the images is of great importance in electron tomography experiments, since the larger the image size, the higher the quality of the image. With the goal of reducing the computation times, this paper introduces different heuristic procedures to obtain feasible solutions for the ordered median problem that provide high-quality images in low computing times. Moreover, some noticeable improvements for the heuristic techniques are developed, taking advantage of the particular versions of the ordered median function that have been proven to be especially suitable for electron tomography image segmentation

Robust mean absolute deviation problems on networks with linear vertex weights

This article deals with incorporating the mean absolute deviation objective function in several robust single facility location models on networks with dynamic evolution of node weights, which are modeled by means of linear functions of a parameter. Specifically, we have considered two robustness criteria applied to the mean absolute deviation problem: the MinMax criterion, and the MinMax regret criterion. For solving the corresponding optimization problems, exact algorithms have been proposed and their complexities have been also analyzed.Ministerio de Ciencia e Innovación MTM2007-67433-C02-(01,02)Ministerio de Ciencia e Innovación MTM2009-14243Ministerio de Ciencia e Innovación MTM2010-19576-C02-(01,02)Ministerio de Ciencia e Innovación DE2009-0057Junta de Andalucía P09-TEP-5022Junta de Andalucía FQM-584

Developing Project Managers’ Transversal Competences Using Building Information Modeling

The emergence of building information modeling (BIM) methodology requires the training of professionals with both specific and transversal skills. In this paper, a project-based learning experience carried out in the context of a project management course at the University of Extremadura is analyzed. To that end, a questionnaire was designed and given to students who participated in the initiative. Results suggest that BIM can be considered a virtual learning environment, from which students value the competences developed. The emotional performance observed was quite flat. Similarly, students valued the usefulness of the initiative. Students expressed a desire for the methodological change of the university classes, and thought that BIM methodology could be useful for other courses. The results obtained show a line of work to be done to improve the training of students and university teaching

New results on minimax regret single facility ordered median location problems on networks

We consider the single facility ordered median location problem with uncertainty in the parameters (weights) defining the objective function. We study two cases. In the first case the uncertain weights belong to a region with a finite number of extreme points, and in the second case they must also satisfy some order constraints and belong to some box, (convex case). To deal with the uncertainty we apply the minimax regret approach, providing strongly polynomial time algorithms to solve these problems

A mathematical programming approach to overlapping community detection

We propose a new optimization model to detect overlapping communities in networks. The model elaborates suggestions contained in Zhang et al. (2007), in which overlapping communities were identified through the use of a fuzzy membership function, calculated as the outcome of a mathematical programming problem. In our approach, we retain the idea of using both mathematical programming and fuzzy membership to detect overlapping communities, but we replace the fuzzy objective function proposed there with another one, based on the Newman and Girvan's definition of modularity. Next, we formulate a new mixed-integer linear programming model to calculate optimal overlapping communities. After some computational tests, we provide some evidence that our new proposal can fix some biases of the previous model, that is, its tendency of calculating communities composed of almost all nodes. Conversely, our new model can reveal other structural properties, such as nodes or communities acting as bridges between communities. Finally, as mathematical programming can be used only for moderate size networks due to its computation time, we proposed two heuristic algorithms to solve the largest instances, that compare favourably to other methodologies. (c) 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Instance and semantic segmentation of point clouds of large metallic truss bridges

Several methods have been developed for the semantic segmentation of reinforced concrete bridges, however, there is a gap for truss bridges. Therefore, in this study a state-of-the-art methodology for the instance and semantic segmentation of point clouds of truss bridges for modelling purposes is presented, which, to the best of the authors' knowledge, is the first such methodology. This algorithm segments each truss element and classifies them as a chord, diagonal, vertical post, interior lateral brace, bottom lateral brace, or strut. The algorithm consists of a sequence of methods, including principal component analysis or clustering, that analyse each point and its neighbours in the point cloud. Case studies show that by adjusting only six manually measured parameters, the algorithm can automatically segment a truss bridge point cloud.Agencia Estatal de Investigación | Ref. PID2021-124236OB-C3Agencia Estatal de Investigación | Ref. RYC2021–033560-IUniversidade de Vigo/CISU