GNOM - Grup d´Optimització Numèrica i Modelització
http://hdl.handle.net/2117/3320
Tue, 01 Dec 2015 00:39:57 GMT2015-12-01T00:39:57ZCalidad 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
Wed, 11 Nov 2015 13:37:28 GMThttp://hdl.handle.net/2117/790372015-11-11T13:37:28ZCobo Valeri, ErikMoher, DavidBoutron, IsabelleGonzález Alastrué, José AntonioSolutions to the facility location problem with general Bernoulli demands
http://hdl.handle.net/2117/78990
Solutions to the facility location problem with general Bernoulli demands
Albareda Sambola, Maria; Fernández Aréizaga, Elena; Saldanha da Gama, Francisco
In this work we address the facility location problem with general Bernoulli demands. Extended formulations are proposed for two different outsourcing policies, which allow using sample average approximation for estimating optimal values. In addition, solutions are obtained heuristically and their values compared with the obtained estimates. Numerical results of a series of computational experiments are presented and analyzed.; In this work we address the facility location problem with general Bernoulli demands. Extended formulations are proposed for two different outsourcing policies, which allow using sample average approximation for estimating optimal values. In addition, solutions are obtained heuristically and their values compared with the obtained estimates. Numerical results of a series of computational experiments are presented and analyzed.
Tue, 10 Nov 2015 18:59:27 GMThttp://hdl.handle.net/2117/789902015-11-10T18:59:27ZAlbareda Sambola, MariaFernández Aréizaga, ElenaSaldanha da Gama, FranciscoIn this work we address the facility location problem with general Bernoulli demands. Extended formulations are proposed for two different outsourcing policies, which allow using sample average approximation for estimating optimal values. In addition, solutions are obtained heuristically and their values compared with the obtained estimates. Numerical results of a series of computational experiments are presented and analyzed.
In this work we address the facility location problem with general Bernoulli demands. Extended formulations are proposed for two different outsourcing policies, which allow using sample average approximation for estimating optimal values. In addition, solutions are obtained heuristically and their values compared with the obtained estimates. Numerical results of a series of computational experiments are presented and analyzed.Parking 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.
Fri, 06 Nov 2015 11:48:44 GMThttp://hdl.handle.net/2117/788862015-11-06T11:48:44ZRoca 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.
Tue, 20 Oct 2015 12:49:02 GMThttp://hdl.handle.net/2117/779752015-10-20T12:49:02ZAlvarez 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.The uncertainty of the energy demand in existing mediterranean urban blocks
http://hdl.handle.net/2117/77469
The uncertainty of the energy demand in existing mediterranean urban blocks
Ortiz, Joana Aina; Salom Tormo, Jaume; Corchero García, Cristina; Guarino, Francesco
The objective of the paper is to describe a stochastic model that has been developed to obtain load
profiles for household electricity. For the study,
several profiles have been generated in order to
simulate the electrical demand of a residential building block or neighbourhood and evaluate the
uncertainty of its energy use. The paper is divided in three different parts: development of the model, validation and determination of the uncertainty demand. In the first parts the basis of the model and how it works is explained. The second one represents the validation of the model, the input data and its results. The last step is focused on a statistical analysis of the electricity demand of a block of dwellings to evaluate minimum number of dwellings needed to estimate the average demand representative of the Mediterranean dwelling with different levels of accuracy
Wed, 07 Oct 2015 17:25:00 GMThttp://hdl.handle.net/2117/774692015-10-07T17:25:00ZOrtiz, Joana AinaSalom Tormo, JaumeCorchero García, CristinaGuarino, FrancescoThe objective of the paper is to describe a stochastic model that has been developed to obtain load
profiles for household electricity. For the study,
several profiles have been generated in order to
simulate the electrical demand of a residential building block or neighbourhood and evaluate the
uncertainty of its energy use. The paper is divided in three different parts: development of the model, validation and determination of the uncertainty demand. In the first parts the basis of the model and how it works is explained. The second one represents the validation of the model, the input data and its results. The last step is focused on a statistical analysis of the electricity demand of a block of dwellings to evaluate minimum number of dwellings needed to estimate the average demand representative of the Mediterranean dwelling with different levels of accuracySistema de gestión energético óptimo para edificios inteligentes con sistemas de generación renovable integrados
http://hdl.handle.net/2117/76528
Sistema de gestión energético óptimo para edificios inteligentes con sistemas de generación renovable integrados
Igualada Gonzalez, Lucia; Corchero García, Cristina; Cruz Zambrano, Miguel
Como solución para los nuevos edificios que desean adquirir la etiqueta de “edificios inteligentes” proponemos un software de gestión energética optima. Se trata de un sistema centralizado capaz de gestionar elementos de generación (por ejemplo, unidades de generación renovables integradas en el edificio), un sistema de almacenamiento y los distintos tipos de demanda que puede generar dicho edificio. Con el objetivo de un control energético total, el sistema consta de tres niveles distintos de gestión y a su vez, con tres modos de funcionamiento diferentes. Para demostrar el funcionamiento de esta herramienta se incluyen los resultados sobre un escenario emulado que consta de una pequeña generación solar, de tres niveles distintos de demanda propia y la demanda de un vehículo eléctrico que a su vez podrá servir de almacenaje energético mientras este permanezca aparcado.
Fri, 28 Aug 2015 09:21:51 GMThttp://hdl.handle.net/2117/765282015-08-28T09:21:51ZIgualada Gonzalez, LuciaCorchero García, CristinaCruz Zambrano, MiguelComo solución para los nuevos edificios que desean adquirir la etiqueta de “edificios inteligentes” proponemos un software de gestión energética optima. Se trata de un sistema centralizado capaz de gestionar elementos de generación (por ejemplo, unidades de generación renovables integradas en el edificio), un sistema de almacenamiento y los distintos tipos de demanda que puede generar dicho edificio. Con el objetivo de un control energético total, el sistema consta de tres niveles distintos de gestión y a su vez, con tres modos de funcionamiento diferentes. Para demostrar el funcionamiento de esta herramienta se incluyen los resultados sobre un escenario emulado que consta de una pequeña generación solar, de tres niveles distintos de demanda propia y la demanda de un vehículo eléctrico que a su vez podrá servir de almacenaje energético mientras este permanezca aparcado.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.
Tue, 21 Jul 2015 09:22:42 GMThttp://hdl.handle.net/2117/762392015-07-21T09:22:42ZAlbareda 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.Interior-point solver for convex separable block-angular problems
http://hdl.handle.net/2117/76231
Interior-point solver for convex separable block-angular problems
Castro Pérez, Jordi
Constraints matrices with block-angular structures are pervasive in Optimization. Interior-point methods have shown to be competitive for these structured problems by exploiting the linear algebra. One of these approaches solved the normal equations using sparse Cholesky factorizations for the block constraints, and a preconditioned conjugate gradient (PCG) for the linking constraints. The preconditioner is based on a power series expansion which approximates the inverse of the matrix of the linking constraints system. In this work we present an efficient solver based on this algorithm. Some of its features are: it solves linearly constrained convex separable problems (linear, quadratic or nonlinear); both Newton and second-order predictor-corrector directions can be used, either with the Cholesky+PCG scheme or with a Cholesky factorization of normal equations; the preconditioner
may include any number of terms of the power series; for any number of these terms, it estimates the spectral radius of the matrix in the power series (which is instrumental for the quality of the precondi-
tioner). The solver has been hooked to SML, a structure-conveying modelling language based on the popular AMPL modeling language. Computational results are reported for some large and/or difficult instances in the literature: (1) multicommodity flow problems; (2) minimum congestion problems; (3) statistical data protection problems using l1 and l2 distances (which are linear and quadratic problems, respectively), and the pseudo-Huber function, a nonlinear approximation to l1 which improves the preconditioner. In the largest instances, of up to 25 millions of variables and 300000 constraints, this approach is from two to three orders of magnitude faster than state-of-the-art linear and quadratic optimization solvers.
Mon, 20 Jul 2015 12:24:19 GMThttp://hdl.handle.net/2117/762312015-07-20T12:24:19ZCastro Pérez, JordiConstraints matrices with block-angular structures are pervasive in Optimization. Interior-point methods have shown to be competitive for these structured problems by exploiting the linear algebra. One of these approaches solved the normal equations using sparse Cholesky factorizations for the block constraints, and a preconditioned conjugate gradient (PCG) for the linking constraints. The preconditioner is based on a power series expansion which approximates the inverse of the matrix of the linking constraints system. In this work we present an efficient solver based on this algorithm. Some of its features are: it solves linearly constrained convex separable problems (linear, quadratic or nonlinear); both Newton and second-order predictor-corrector directions can be used, either with the Cholesky+PCG scheme or with a Cholesky factorization of normal equations; the preconditioner
may include any number of terms of the power series; for any number of these terms, it estimates the spectral radius of the matrix in the power series (which is instrumental for the quality of the precondi-
tioner). The solver has been hooked to SML, a structure-conveying modelling language based on the popular AMPL modeling language. Computational results are reported for some large and/or difficult instances in the literature: (1) multicommodity flow problems; (2) minimum congestion problems; (3) statistical data protection problems using l1 and l2 distances (which are linear and quadratic problems, respectively), and the pseudo-Huber function, a nonlinear approximation to l1 which improves the preconditioner. In the largest instances, of up to 25 millions of variables and 300000 constraints, this approach is from two to three orders of magnitude faster than state-of-the-art linear and quadratic optimization solvers.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.
Thu, 18 Jun 2015 14:05:36 GMThttp://hdl.handle.net/2117/283432015-06-18T14:05:36ZAlbareda 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.
Tue, 16 Jun 2015 16:38:50 GMThttp://hdl.handle.net/2117/283262015-06-16T16:38:50ZBaena, 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.