Optimization assessment of the energy performance of a BIPV/T-PCM system using Genetic Algorithms

ABSTRACT: In this paper, a BIPV/T-PCM installed in an office building façade is investigated to approach the system efficiency optimization using Genetic Algorithm method. Based on an updated mathematical model, theoretical simulation has been conducted for BIPV/T-PCM in this case for the existing system set-up (geometry-air cavity width, ventilation, system layers). Furthermore, field testing for this case has also been performed to validate the model, and then the simulated and experimental results are compared and found in considerably good agreement. The overall energy efficiency of the system was evaluated for winter and summer condition adopting different utilization strategies and optimization variables have been identified. The thermal and electric efficiencies were calculated based on the optimization variables and the results shown that the system can achieve a maximum overall efficiency of 64% with winter configuration and 32% with summer configuration.info:eu-repo/semantics/publishedVersio

Multi-depot rural postman problems

The final publication is available at Springer via http://dx.doi.org/10.1007/s11750-016-0434-zThis paper studies multi-depot rural postman problems on an undirected graph. These problems extend the well-known undirected rural postman problem to the case where there are several depots instead of just one. Linear integer programming formulations that only use binary variables are proposed for the problem that minimizes the overall routing costs and for the model that minimizes the length of the longest route. An exact branch-and-cut algorithm is presented for each considered model, where violated constraints of both types are separated in polynomial time. Despite the difficulty of the problems, the numerical results from a series of computational experiments with various types of instances illustrate a quite good behavior of the algorithms. When the overall routing costs are minimized, over 43 % of the instances were optimally solved at the root node, and 95 % were solved at termination, most of them with a small additional computational effort. When the length of the longest route is minimized, over 25 % of the instances were optimally solved at the root node, and 99 % were solved at termination.Peer ReviewedPostprint (author's final draft

An X-ray Study of Local Infrared Bright Galaxies

We are carrying out detailed study of the X-ray and infrared (IR) properties of a sample of local (d < 70 Mpc) luminous infrared galaxies (LIRGs) using XMM-Newton and Spitzer (imaging and spectroscopy). The main goal is to study the extreme processes of star formation and/or active galactic nuclei (AGN) taking place in this cosmologically important class of galaxies. In this proceedings we present the preliminary results obtained from the analysis of the XMM-Newton X-ray images and the X-ray spectral modeling.Comment: 5 pages, to appear in Highlights of Spanish Astrophysics VI, Proceedings of the IX Scientific Meeting of the Spanish Astronomical Society held on September 13-17, 2010, in Madrid, Spai

Exact solution of several families of location-arc routing problems

We model and solve several families of location-arc routing problems on an undirected graph. These problems extend the multidepot rural postman problem to the case where the depots are not fixed. The aim is to select the facility locations and to construct a set of routes traversing each required edge of the graph, where each route starts and ends at the same facility. The models differ from each other in their objective functions and on whether they include a capacity constraint. Alternative formulations are presented that use only binary variables, and are valid even when the input graph is not complete. This applies, in particular, to a compact two-index formulation for problems minimizing the overall routing costs, with or without facility setup costs. This formulation incorporates a newset of constraints that force the routes to be consistent and return to their original depots. A polyhedral study is presented for some of the formulations, which indicates that themain families of constraints are facet defining. All formulations are solved by branch and cut, and instances with up to 200 vertices are solved to optimality. Despite the difficulty of the problems, the numerical results demonstrate the good performance of the algorithm.</p

Exact solution of several families of location-arc routing problems

We model and solve several families of location-arc routing problems on an undirected graph. These problems extend the multidepot rural postman problem to the case where the depots are not fixed. The aim is to select the facility locations and to construct a set of routes traversing each required edge of the graph, where each route starts and ends at the same facility. The models differ from each other in their objective functions and on whether they include a capacity constraint. Alternative formulations are presented that use only binary variables, and are valid even when the input graph is not complete. This applies, in particular, to a compact two-index formulation for problems minimizing the overall routing costs, with or without facility setup costs. This formulation incorporates a newset of constraints that force the routes to be consistent and return to their original depots. A polyhedral study is presented for some of the formulations, which indicates that themain families of constraints are facet defining. All formulations are solved by branch and cut, and instances with up to 200 vertices are solved to optimality. Despite the difficulty of the problems, the numerical results demonstrate the good performance of the algorithm.</p

A branch-and-cut algorithm for the multidepot rural postman problem

This paper considers the Multidepot Rural Postman Problem, an extension of the classical Rural Postman Problem in which there are several depots instead of only one. The aim is to construct a minimum cost set of routes traversing each required edge of the graph, where each route starts and ends at the same depot. The paper makes the following scientific contributions: (i) It presents optimality conditions and a worst case analysis for the problem; (ii) It proposes a compact integer linear programming formulation containing only binary variables, as well as a polyhedral analysis; (iii) It develops a branch-and-cut algorithm that includes several new exact and heuristic separation procedures. Instances involving up to four depots, 744 vertices, and 1,315 edges are solved to optimality. These instances contain up to 140 required components and 1,000 required edges.Peer ReviewedPostprint (author's final draft

Improving detection of apneic events by learning from examples and treatment of missing data

The final publication is available at IOS Press through http://dx.doi.org/10.3233/978-1-61499-474-9-213[Abstract] This paper presents a comparative study over the respiratory pattern classification task involving three missing data imputation techniques, and four different machine learning algorithms. The main goal was to find a classifier that achieves the best accuracy results using a scalable imputation method in comparison to the method used in a previous work of the authors. The results obtained show that the Self-organization maps imputation method allows any classifier to achieve improvements over the rest of the imputation methods, and that the Feedforward neural network classifier offers the best performance regardless the imputation method used

Diseño de rutas de recogida de residuos sólidos urbanos en el área metropolitana de Barcelona

Los problemas aso ciados a la recogida de residuos sólidos urbanos son muy variados. En este traba jo se presenta el problema de diseño de itinerarios de recogida y se muestran los resultados ofrecidos p or un pro cedimiento basado en colonias de hormigas a la recogida en un núcleo urbano del Área Metrop olitana de Barcelona.Postprint (published version

Automatic classification of respiratory patterns involving missing data imputation techniques

[Abstract] A comparative study of the respiratory pattern classification task, involving five missing data imputation techniques and several machine learning algorithms is presented in this paper. The main goal was to find a classifier that achieves the best accuracy results using a scalable imputation method in comparison to the method used in a previous work of the authors. The results obtained show that in general, the Self-Organising Map imputation method allows non-tree based classifiers to achieve improvements over the rest of the imputation methods in terms of the classification accuracy, and that the Feedforward neural network and the Random Forest classifiers offer the best performance regardless of the imputation method used. The improvements in terms of accuracy over the previous work of the authors are limited but the Feed Forward neural network model achieves promising results.Ministerio de Economía y Competitividad; TIN 2013-40686-PXunta de Galicia; GRC2014/35