Articles de revista
http://hdl.handle.net/2117/3321
2015-11-28T15:08:29ZCalidad y transparencia de Fisioterapia mediante guías de publicación
http://hdl.handle.net/2117/79037
Calidad y transparencia de Fisioterapia mediante guías de publicación
Cobo Valeri, Erik; Moher, David; Boutron, Isabelle; González Alastrué, José Antonio
2015-11-11T13:37:28ZCobo Valeri, ErikMoher, DavidBoutron, IsabelleGonzález Alastrué, José AntonioParking slot assignment for urban distribution: models and formulations
http://hdl.handle.net/2117/78886
Parking slot assignment for urban distribution: models and formulations
Roca Riu, Mireia; Fernández Aréizaga, Elena; Estrada Romeu, Miguel Ángel
A key element to enhance urban distribution is the adequate management of parking space, particularly for loading and unloading operations. An in-advance booking system able to be adjusted to users needs can be a very useful tool for city councils. Such a tool should be fed with criteria for allocating requests to time slots. In this paper we discuss alternative criteria for the parking slot assignment problem for urban distribution and we propose the use of mathematical programming formulations to model them. Several models are proposed, analyzed and compared among them. Extensive computational experience is presented with a detailed analysis and comparison, which provides quantitative indicators of the quality of each of the proposed models.
2015-11-06T11:48:44ZRoca Riu, MireiaFernández Aréizaga, ElenaEstrada Romeu, Miguel ÁngelA key element to enhance urban distribution is the adequate management of parking space, particularly for loading and unloading operations. An in-advance booking system able to be adjusted to users needs can be a very useful tool for city councils. Such a tool should be fed with criteria for allocating requests to time slots. In this paper we discuss alternative criteria for the parking slot assignment problem for urban distribution and we propose the use of mathematical programming formulations to model them. Several models are proposed, analyzed and compared among them. Extensive computational experience is presented with a detailed analysis and comparison, which provides quantitative indicators of the quality of each of the proposed models.The recoverable robust facility location problem
http://hdl.handle.net/2117/77975
The recoverable robust facility location problem
Alvarez Miranda, Eduardo; Fernández Aréizaga, Elena; Ljubic, Ivana
This work deals with a facility location problem in which location and allocation (transportation) policy is defined in two stages such that a first-stage solution should be robust against the possible realizations (scenarios) of the input data that can only be revealed in a second stage. This solution should be robust enough so that it can be recovered promptly and at low cost in the second stage. In contrast to some related modeling approaches from the literature, this new recoverable robust model is more general in terms of the considered data uncertainty; it can address situations in which uncertainty may be present in any of the following four categories: provider-side uncertainty, receiver-side uncertainty, uncertainty in-between, and uncertainty with respect to the cost parameters.; For this novel problem, a sophisticated branch-and-cut framework based on Benders decomposition is designed and complemented by several non-trivial enhancements, including scenario sorting, dual lifting, branching priorities, matheuristics and zero-half cuts. Two large sets of instances that incorporate spatial and demographic information of countries such as Germany and US (transportation) and Bangladesh and the Philippines (disaster management) are introduced. They are used to analyze in detail the characteristics of the proposed model and the obtained solutions as well as the effectiveness, behavior and limitations of the designed algorithm. (C) 2015 Elsevier Ltd. All rights reserved.
2015-10-20T12:49:02ZAlvarez Miranda, EduardoFernández Aréizaga, ElenaLjubic, IvanaThis work deals with a facility location problem in which location and allocation (transportation) policy is defined in two stages such that a first-stage solution should be robust against the possible realizations (scenarios) of the input data that can only be revealed in a second stage. This solution should be robust enough so that it can be recovered promptly and at low cost in the second stage. In contrast to some related modeling approaches from the literature, this new recoverable robust model is more general in terms of the considered data uncertainty; it can address situations in which uncertainty may be present in any of the following four categories: provider-side uncertainty, receiver-side uncertainty, uncertainty in-between, and uncertainty with respect to the cost parameters.; For this novel problem, a sophisticated branch-and-cut framework based on Benders decomposition is designed and complemented by several non-trivial enhancements, including scenario sorting, dual lifting, branching priorities, matheuristics and zero-half cuts. Two large sets of instances that incorporate spatial and demographic information of countries such as Germany and US (transportation) and Bangladesh and the Philippines (disaster management) are introduced. They are used to analyze in detail the characteristics of the proposed model and the obtained solutions as well as the effectiveness, behavior and limitations of the designed algorithm. (C) 2015 Elsevier Ltd. All rights reserved.When centers can fail: a close second opportunity
http://hdl.handle.net/2117/76239
When centers can fail: a close second opportunity
Albareda Sambola, Maria; Hinojosa, Yolanda; Marín, Alfredo; Puerto Albandoz, Justo
This paper presents the p-next center problem, which aims to locate p out of n centers so as to minimize the maximum cost of allocating customers to backup centers. In this problem it is assumed that centers can fail and customers only realize that their closest (reference) center has failed upon arrival. When this happens, they move to their backup center, i.e., to the center that is closest to the reference center. Hence, minimizing the maximum travel distance from a customer to its backup center can be seen as an alternative approach to handle humanitarian logistics, that hedges customers against severe scenario deteriorations when a center fails.
For this extension of the p-center problem we have developed several different integer programming formulations with their corresponding strengthenings based on valid inequalities and variable fixing. The suitability of these formulations for solving the p-next center problem using standard software is analyzed in a series of computational experiments. These experiments were carried out using instances taken from the previous discrete location literature.
2015-07-21T09:22:42ZAlbareda Sambola, MariaHinojosa, YolandaMarín, AlfredoPuerto Albandoz, JustoThis paper presents the p-next center problem, which aims to locate p out of n centers so as to minimize the maximum cost of allocating customers to backup centers. In this problem it is assumed that centers can fail and customers only realize that their closest (reference) center has failed upon arrival. When this happens, they move to their backup center, i.e., to the center that is closest to the reference center. Hence, minimizing the maximum travel distance from a customer to its backup center can be seen as an alternative approach to handle humanitarian logistics, that hedges customers against severe scenario deteriorations when a center fails.
For this extension of the p-center problem we have developed several different integer programming formulations with their corresponding strengthenings based on valid inequalities and variable fixing. The suitability of these formulations for solving the p-next center problem using standard software is analyzed in a series of computational experiments. These experiments were carried out using instances taken from the previous discrete location literature.The reliable p-median problem with at-facility service
http://hdl.handle.net/2117/28343
The reliable p-median problem with at-facility service
Albareda Sambola, Maria; Hinojosa, Yolanda; Puerto Albandoz, Justo
This paper deals with a discrete facility location model where service is provided at the facility sites. It is assumed that facilities can fail and customers do not have information on failures before reaching them. As a consequence, they may need to visit more than one facility, following an optimized search scheme, in order to get service. The goal of the problem is to locate p facilities in order to minimize the expected total travel cost. The paper presents two alternative mathematical programming formulations for this problem and proposes a matheuristic based on a network flow model to provide solutions to it. The computational burden of the presented formulations is tested and compared on a test-bed of instances.
2015-06-18T14:05:36ZAlbareda Sambola, MariaHinojosa, YolandaPuerto Albandoz, JustoThis paper deals with a discrete facility location model where service is provided at the facility sites. It is assumed that facilities can fail and customers do not have information on failures before reaching them. As a consequence, they may need to visit more than one facility, following an optimized search scheme, in order to get service. The goal of the problem is to locate p facilities in order to minimize the expected total travel cost. The paper presents two alternative mathematical programming formulations for this problem and proposes a matheuristic based on a network flow model to provide solutions to it. The computational burden of the presented formulations is tested and compared on a test-bed of instances.Fix-and-relax approaches for controlled tabular adjustment
http://hdl.handle.net/2117/28326
Fix-and-relax approaches for controlled tabular adjustment
Baena, Daniel; Castro Pérez, Jordi; González Alastrué, José Antonio
Controlled tabular adjustment (CIA) is a relatively new protection technique for tabular data protection. CTA formulates a mixed integer linear programming problem, which is challenging for tables of moderate size. Even finding a feasible initial solution may be a challenging task for large instances. On the other hand, end users of tabular data protection techniques give priority to fast executions and are thus satisfied in practice with suboptimal solutions. This work has two goals. First, the fix-and-relax (FR) strategy is applied to obtain good feasible initial solutions to large CTA instances. FR is based on partitioning the set of binary variables into clusters to selectively explore a smaller branch-and-cut tree. Secondly, the FR solution is used as a warm start for a block coordinate descent (BCD) heuristic (approach named FR+BCD); BCD was confirmed to be a good option for large CTA instances in an earlier paper by the second and third co-authors (Comput Oper Res 2011;38:1826-35 [23]). We report extensive computational results on a set of real-world and synthetic CTA instances. FR is shown to be competitive compared to CPLEX branch-and-cut in terms of quickly finding either a feasible solution or a good upper bound. FR+BCD improved the quality of FR solutions for approximately 25% and 50% of the synthetic and real-world instances, respectively. FR or FR+BCD provided similar or better solutions in less CPU time than CPLEX for 73% of the difficult real-world instances. (C) 2015 Elsevier Ltd. All rights reserved.
2015-06-16T16:38:50ZBaena, DanielCastro Pérez, JordiGonzález Alastrué, José AntonioControlled tabular adjustment (CIA) is a relatively new protection technique for tabular data protection. CTA formulates a mixed integer linear programming problem, which is challenging for tables of moderate size. Even finding a feasible initial solution may be a challenging task for large instances. On the other hand, end users of tabular data protection techniques give priority to fast executions and are thus satisfied in practice with suboptimal solutions. This work has two goals. First, the fix-and-relax (FR) strategy is applied to obtain good feasible initial solutions to large CTA instances. FR is based on partitioning the set of binary variables into clusters to selectively explore a smaller branch-and-cut tree. Secondly, the FR solution is used as a warm start for a block coordinate descent (BCD) heuristic (approach named FR+BCD); BCD was confirmed to be a good option for large CTA instances in an earlier paper by the second and third co-authors (Comput Oper Res 2011;38:1826-35 [23]). We report extensive computational results on a set of real-world and synthetic CTA instances. FR is shown to be competitive compared to CPLEX branch-and-cut in terms of quickly finding either a feasible solution or a good upper bound. FR+BCD improved the quality of FR solutions for approximately 25% and 50% of the synthetic and real-world instances, respectively. FR or FR+BCD provided similar or better solutions in less CPU time than CPLEX for 73% of the difficult real-world instances. (C) 2015 Elsevier Ltd. All rights reserved.Methodology for the economic optimisation of energy storage systems for frequency support in wind power plants
http://hdl.handle.net/2117/28095
Methodology for the economic optimisation of energy storage systems for frequency support in wind power plants
Johnstone, Lewis; Díaz González, Francisco; Gomis Bellmunt, Oriol; Corchero García, Cristina; Cruz Zambrano, Miguel
This paper proposes a methodology for the economic optimisation of the sizing of Energy Storage Systems (ESSs) whilst enhancing the participation of Wind Power Plants (WPP) in network primary frequency control support. The methodology was designed flexibly, so it can be applied to different energy markets and to include different ESS technologies. The methodology includes the formulation and solving of a Linear Programming (LP) problem.; The methodology was applied to the particular case of a 50 MW WPP, equipped with a Vanadium Redox Flow battery (VRB) in the UK energy market. Analysis is performed considering real data on the UK regular energy market and the UK frequency response market. Data for wind power generation and energy storage costs are estimated from literature.; Results suggest that, under certain assumptions, ESSs can be profitable for the operator of a WPP that is providing frequency response. The ESS provides power reserves such that the WPP can generate close to the maximum energy available. The solution of the optimisation problem establishes that an ESS with a power rating of 5.3 MW and energy capacity of about 3 MW h would be enough to provide such service whilst maximising the incomes for the WPP operator considering the regular and frequency regulation UK markets. (C) 2014 Elsevier Ltd. All rights reserved.
2015-05-28T12:55:30ZJohnstone, LewisDíaz González, FranciscoGomis Bellmunt, OriolCorchero García, CristinaCruz Zambrano, MiguelThis paper proposes a methodology for the economic optimisation of the sizing of Energy Storage Systems (ESSs) whilst enhancing the participation of Wind Power Plants (WPP) in network primary frequency control support. The methodology was designed flexibly, so it can be applied to different energy markets and to include different ESS technologies. The methodology includes the formulation and solving of a Linear Programming (LP) problem.; The methodology was applied to the particular case of a 50 MW WPP, equipped with a Vanadium Redox Flow battery (VRB) in the UK energy market. Analysis is performed considering real data on the UK regular energy market and the UK frequency response market. Data for wind power generation and energy storage costs are estimated from literature.; Results suggest that, under certain assumptions, ESSs can be profitable for the operator of a WPP that is providing frequency response. The ESS provides power reserves such that the WPP can generate close to the maximum energy available. The solution of the optimisation problem establishes that an ESS with a power rating of 5.3 MW and energy capacity of about 3 MW h would be enough to provide such service whilst maximising the incomes for the WPP operator considering the regular and frequency regulation UK markets. (C) 2014 Elsevier Ltd. All rights reserved.A biased random-key genetic algorithm for the capacitated minimum spanning tree problem
http://hdl.handle.net/2117/27676
A biased random-key genetic algorithm for the capacitated minimum spanning tree problem
Ruiz Ruiz, Hector Efrain; Albareda Sambola, Maria; Fernández Aréizaga, Elena; Resende, Mauricio G. C.
This paper focuses on the capacitated minimum spanning tree(CMST)problem.Given a central
processor and a set of remote terminals with specified demands for traffic that must flow between the central processor and terminals,the goal is to design a minimum cost network to carry this demand.
Potential links exist between any pair of terminals and between the central processor and the terminals.
Each potential link can be included in the design at a given cost.The CMST problem is to design a
minimum-cost network connecting the terminals with the central processor so that the flow on any arc of the network is at most Q. A biased random-keygenetic algorithm(BRKGA)is a metaheuristic for combinatorial optimization which evolves a population of random vectors that encode solutions to the combinatorial optimization problem.This paper explores several solution encodings as well as different
strategies for some steps of the algorithm and finally proposes a BRKGA heuristic for the CMST problem.
Computational experiments are presented showing the effectivenes sof the approach:Seven newbest-
known solutions are presented for the set of benchmark instances used in the experiments.
2015-04-29T16:50:22ZRuiz Ruiz, Hector EfrainAlbareda Sambola, MariaFernández Aréizaga, ElenaResende, Mauricio G. C.This paper focuses on the capacitated minimum spanning tree(CMST)problem.Given a central
processor and a set of remote terminals with specified demands for traffic that must flow between the central processor and terminals,the goal is to design a minimum cost network to carry this demand.
Potential links exist between any pair of terminals and between the central processor and the terminals.
Each potential link can be included in the design at a given cost.The CMST problem is to design a
minimum-cost network connecting the terminals with the central processor so that the flow on any arc of the network is at most Q. A biased random-keygenetic algorithm(BRKGA)is a metaheuristic for combinatorial optimization which evolves a population of random vectors that encode solutions to the combinatorial optimization problem.This paper explores several solution encodings as well as different
strategies for some steps of the algorithm and finally proposes a BRKGA heuristic for the CMST problem.
Computational experiments are presented showing the effectivenes sof the approach:Seven newbest-
known solutions are presented for the set of benchmark instances used in the experiments.Stochastic model for electrical loads in Mediterranean residential building: validation and applications
http://hdl.handle.net/2117/27403
Stochastic model for electrical loads in Mediterranean residential building: validation and applications
Ortiz, Joana Aina; Guarino, Francesco; Salom Tormo, Jaume; Corchero García, Cristina; Cellura, Maurizio
A major issue in modelling the electrical load of residential building is reproducing the variability between dwellings due to the stochastic use of different electrical equipment. In that sense and with the objective to reproduce this variability, a stochastic model to obtain load profiles of household electricity is developed. The model is based on a probabilistic approach and is developed using data from the Mediterranean region of Spain. A detailed validation of the model has been done, analysing and comparing the results with Spanish and European data. The results of the validation show that the model is able to reproduce the most important features of the residential electrical consumption, especially the particularities of the Mediterranean countries. The final part of the paper is focused on the potential applications of the models, and some examples are proposed. The model is useful to simulate a cluster of buildings or individual households. The model allows obtaining synthetic profiles representing the most important characteristics of the mean dwelling, by means of a stochastic approach. The inputs of the proposed model are adapted to energy labelling information of the electric devices. An example case is presented considering a dwelling with high performance equipment.
2015-04-16T18:55:29ZOrtiz, Joana AinaGuarino, FrancescoSalom Tormo, JaumeCorchero García, CristinaCellura, MaurizioA major issue in modelling the electrical load of residential building is reproducing the variability between dwellings due to the stochastic use of different electrical equipment. In that sense and with the objective to reproduce this variability, a stochastic model to obtain load profiles of household electricity is developed. The model is based on a probabilistic approach and is developed using data from the Mediterranean region of Spain. A detailed validation of the model has been done, analysing and comparing the results with Spanish and European data. The results of the validation show that the model is able to reproduce the most important features of the residential electrical consumption, especially the particularities of the Mediterranean countries. The final part of the paper is focused on the potential applications of the models, and some examples are proposed. The model is useful to simulate a cluster of buildings or individual households. The model allows obtaining synthetic profiles representing the most important characteristics of the mean dwelling, by means of a stochastic approach. The inputs of the proposed model are adapted to energy labelling information of the electric devices. An example case is presented considering a dwelling with high performance equipment.Renewable energies in medium-term power planning
http://hdl.handle.net/2117/26280
Renewable energies in medium-term power planning
Marí Tomàs, Laura; Nabona Francisco, Narcís
The medium-term generation planning over a yearly horizon for generation portfolios including hydro generation and non-dispatchable renewables such as wind power and solar photovoltaic generation reveals how the penetration of these technologies reduces the share of other technologies and how it changes the profits and the profit spread in liberalized electricity markets. The matching of the load duration curves in different periods and the forced outages of generation units are here addressed through probabilistic methods and a heuristic is employed to guess which of the load-matching constraints may be active at the solution. There are well-established models for hydro generation in medium-term planning, but specific models are necessary to account for wind power and photovoltaic generation. A proposal for these is made in this work, which is suitable for use in the load duration curve matching through probabilistic methods. Moreover the stochasticity of the renewable sources requires the use of stochastic programming employing scenario trees, here developed using quasi-Monte Carlo techniques. Medium-term pumping schemes are also considered. Several realistic cases will be solved for two behavioral principles of a pure pool market: endogenous cartel and equilibrium.
2015-02-10T11:08:41ZMarí Tomàs, LauraNabona Francisco, NarcísThe medium-term generation planning over a yearly horizon for generation portfolios including hydro generation and non-dispatchable renewables such as wind power and solar photovoltaic generation reveals how the penetration of these technologies reduces the share of other technologies and how it changes the profits and the profit spread in liberalized electricity markets. The matching of the load duration curves in different periods and the forced outages of generation units are here addressed through probabilistic methods and a heuristic is employed to guess which of the load-matching constraints may be active at the solution. There are well-established models for hydro generation in medium-term planning, but specific models are necessary to account for wind power and photovoltaic generation. A proposal for these is made in this work, which is suitable for use in the load duration curve matching through probabilistic methods. Moreover the stochasticity of the renewable sources requires the use of stochastic programming employing scenario trees, here developed using quasi-Monte Carlo techniques. Medium-term pumping schemes are also considered. Several realistic cases will be solved for two behavioral principles of a pure pool market: endogenous cartel and equilibrium.