GNOM  Grup d´Optimització Numèrica i Modelització
http://hdl.handle.net/2117/3320
Sat, 13 Feb 2016 00:48:19 GMT
20160213T00:48:19Z

Fixedcharge facility location problems in location science
http://hdl.handle.net/2117/82657
Fixedcharge facility location problems in location science
Fernández Aréizaga, Elena; Landete, Mercedes
FixedCharge Facility Location Problems are among core problems in Location Science. There is a finite set of users with demand of service and a finite set of potential locations for the facilities that will offer service to users. Two types of decisions must be made: Location decisions determine where to establish the facilities whereas allocation decisions dictate how to satisfy the users demand from the established facilities. Potential applications of various types arise in many different contexts. We provide an overview of the main elements that may intervene in the modeling and the solution process of FixedCharge Facility Location Problems, namely, modeling hypotheses and their implications, characteristics of formulations and their relation to other formulations, properties of the domains, and appropriate solution techniques.
Mon, 08 Feb 2016 10:02:41 GMT
http://hdl.handle.net/2117/82657
20160208T10:02:41Z
Fernández Aréizaga, Elena
Landete, Mercedes
FixedCharge Facility Location Problems are among core problems in Location Science. There is a finite set of users with demand of service and a finite set of potential locations for the facilities that will offer service to users. Two types of decisions must be made: Location decisions determine where to establish the facilities whereas allocation decisions dictate how to satisfy the users demand from the established facilities. Potential applications of various types arise in many different contexts. We provide an overview of the main elements that may intervene in the modeling and the solution process of FixedCharge Facility Location Problems, namely, modeling hypotheses and their implications, characteristics of formulations and their relation to other formulations, properties of the domains, and appropriate solution techniques.

Economic analysis of battery electric storage systems operating in electricity markets
http://hdl.handle.net/2117/82524
Economic analysis of battery electric storage systems operating in electricity markets
Heredia, F.Javier (Francisco Javier); Riera, Jordi; Mata, Montserrat; Escuer, Joan; Romeu, Jordi
Battery electric storage systems (BESS) in the range of 110 MWh is a key technology allowing a more efficient operation of small electricity market producer. The aim of this work is to assess the economic viability of Liion based BESS systems for small electricity producers. The results of the expost economic analysis performed with real data from the Iberian Electricity Market shows the economic viability of a Liion based BESS thanks to the optimal operation in dayahead and ancillary electricity markets.
Wed, 03 Feb 2016 18:04:17 GMT
http://hdl.handle.net/2117/82524
20160203T18:04:17Z
Heredia, F.Javier (Francisco Javier)
Riera, Jordi
Mata, Montserrat
Escuer, Joan
Romeu, Jordi
Battery electric storage systems (BESS) in the range of 110 MWh is a key technology allowing a more efficient operation of small electricity market producer. The aim of this work is to assess the economic viability of Liion based BESS systems for small electricity producers. The results of the expost economic analysis performed with real data from the Iberian Electricity Market shows the economic viability of a Liion based BESS thanks to the optimal operation in dayahead and ancillary electricity markets.

On the collaboration uncapacitated arc routing problem
http://hdl.handle.net/2117/81939
On the collaboration uncapacitated arc routing problem
Fernández Aréizaga, Elena; Fontana, Dario; Speranza, M. Grazia
© 2015 Elsevier Ltd. All rights reserved.
This paper introduces a new arc routing problem for the optimization of a collaboration scheme among carriers. This yields to the study of a profitable uncapacitated arc routing problem with multiple depots, where carriers collaborate to improve the profit gained. In the first model the goal is the maximization of the total profit of the coalition of carriers, independently of the individual profit of each carrier. Then, a lower bound on the individual profit of each carrier is included. This lower bound may represent the profit of the carrier in the case no collaboration is implemented. The models are formulated as integer linear programs and solved through a branchandcut algorithm. Theoretical results, concerning the computational complexity, the impact of collaboration on profit and a game theoretical perspective, are provided. The models are tested on a set of 971 instances generated from 118 benchmark instances for the Privatized Rural Postman Problem, with up to 102 vertices. All the 971 instances are solved to optimality within few seconds.
Mon, 25 Jan 2016 09:33:18 GMT
http://hdl.handle.net/2117/81939
20160125T09:33:18Z
Fernández Aréizaga, Elena
Fontana, Dario
Speranza, M. Grazia
© 2015 Elsevier Ltd. All rights reserved.
This paper introduces a new arc routing problem for the optimization of a collaboration scheme among carriers. This yields to the study of a profitable uncapacitated arc routing problem with multiple depots, where carriers collaborate to improve the profit gained. In the first model the goal is the maximization of the total profit of the coalition of carriers, independently of the individual profit of each carrier. Then, a lower bound on the individual profit of each carrier is included. This lower bound may represent the profit of the carrier in the case no collaboration is implemented. The models are formulated as integer linear programs and solved through a branchandcut algorithm. Theoretical results, concerning the computational complexity, the impact of collaboration on profit and a game theoretical perspective, are provided. The models are tested on a set of 971 instances generated from 118 benchmark instances for the Privatized Rural Postman Problem, with up to 102 vertices. All the 971 instances are solved to optimality within few seconds.

A BRILS metaheuristic for nonsmooth flowshop problems with failurerisk costs
http://hdl.handle.net/2117/81738
A BRILS metaheuristic for nonsmooth flowshop problems with failurerisk costs
Ferrer Biosca, Alberto; Guimarans, Daniel; Ramalhino Lourenço, Helena; Juan Pérez, Ángel Alejandro
This paper analyzes a realistic variant of the Permutation FlowShop Problem (PFSP) by considering a nonsmooth objective function that takes into account not only the traditional makespan cost but also failurerisk costs due to uninterrupted operation of machines. After completing a literature review on the issue, the paper formulates an original mathematical model to describe this new PFSP variant. Then, a BiasedRandomized Iterated Local Search (BRILS) algorithm is proposed as an efficient solving approach. An oriented (biased) random behavior is introduced in the wellknown NEH heuristic to generate an initial solution. From this initial solution, the algorithm is able to generate a large number of alternative good solutions without requiring a complex setting of parameters. The relative simplicity of our approach is particularly useful in the presence of nonsmooth objective functions, for which exact optimization methods may fail to reach their full potential. The gains of considering failurerisk costs during the exploration of the solution space are analyzed throughout a series of computational experiments. To promote reproducibility, these experiments are based on a set of traditional benchmark instances. Moreover, the performance of the proposed algorithm is compared against other stateoftheart metaheuristic approaches, which have been conveniently adapted to consider failurerisk costs during the solving process. The proposed BRILS approach can be easily extended to other combinatorial optimization problems with similar nonsmooth objective functions.
Wed, 20 Jan 2016 13:51:16 GMT
http://hdl.handle.net/2117/81738
20160120T13:51:16Z
Ferrer Biosca, Alberto
Guimarans, Daniel
Ramalhino Lourenço, Helena
Juan Pérez, Ángel Alejandro
This paper analyzes a realistic variant of the Permutation FlowShop Problem (PFSP) by considering a nonsmooth objective function that takes into account not only the traditional makespan cost but also failurerisk costs due to uninterrupted operation of machines. After completing a literature review on the issue, the paper formulates an original mathematical model to describe this new PFSP variant. Then, a BiasedRandomized Iterated Local Search (BRILS) algorithm is proposed as an efficient solving approach. An oriented (biased) random behavior is introduced in the wellknown NEH heuristic to generate an initial solution. From this initial solution, the algorithm is able to generate a large number of alternative good solutions without requiring a complex setting of parameters. The relative simplicity of our approach is particularly useful in the presence of nonsmooth objective functions, for which exact optimization methods may fail to reach their full potential. The gains of considering failurerisk costs during the exploration of the solution space are analyzed throughout a series of computational experiments. To promote reproducibility, these experiments are based on a set of traditional benchmark instances. Moreover, the performance of the proposed algorithm is compared against other stateoftheart metaheuristic approaches, which have been conveniently adapted to consider failurerisk costs during the solving process. The proposed BRILS approach can be easily extended to other combinatorial optimization problems with similar nonsmooth objective functions.

Mathematical programming approaches for classes of random network problems
http://hdl.handle.net/2117/81111
Mathematical programming approaches for classes of random network problems
Castro Pérez, Jordi; Nasini, Stefano
Random simulations from complicated combinatorial sets are often needed in many classes of stochastic problems. This is particularly true in the analysis of complex networks, where researchers are usually interested in assessing whether an observed network feature is expected to be found within families of networks under some hypothesis (named conditional random networks, i.e., networks satisfying some linear constraints). This work presents procedures to generate networks with specified structural properties which rely on the Solution of classes of integer optimization problems. We show that, for many of them, the constraints matrices are totally unimodular, allowing the efficient generation of conditional random networks by specialized interiorpoint methods. The computational results suggest that the proposed methods can represent a general framework for the efficient generation of random networks even beyond the models analyzed in this paper. This work also opens the posSibility for other applications of mathematical programming in the analysis of complex networks. (C) 2015 Elsevier B.V. All rights reserved.
Thu, 07 Jan 2016 16:32:22 GMT
http://hdl.handle.net/2117/81111
20160107T16:32:22Z
Castro Pérez, Jordi
Nasini, Stefano
Random simulations from complicated combinatorial sets are often needed in many classes of stochastic problems. This is particularly true in the analysis of complex networks, where researchers are usually interested in assessing whether an observed network feature is expected to be found within families of networks under some hypothesis (named conditional random networks, i.e., networks satisfying some linear constraints). This work presents procedures to generate networks with specified structural properties which rely on the Solution of classes of integer optimization problems. We show that, for many of them, the constraints matrices are totally unimodular, allowing the efficient generation of conditional random networks by specialized interiorpoint methods. The computational results suggest that the proposed methods can represent a general framework for the efficient generation of random networks even beyond the models analyzed in this paper. This work also opens the posSibility for other applications of mathematical programming in the analysis of complex networks. (C) 2015 Elsevier B.V. All rights reserved.

A cuttingplane approach for largescale capacitated multiperiod facility location using a specialized interiorpoint method
http://hdl.handle.net/2117/80887
A cuttingplane approach for largescale capacitated multiperiod facility location using a specialized interiorpoint method
Castro Pérez, Jordi; Nasini, Stefano; Saldanha da Gama, Francisco
We propose a cuttingplane approach (namely, Benders decomposition) for a class of capacitated multiperiod facility location problems. The novelty of this approach lies on the use of a specialized interiorpoint method for solving the Benders subproblems. The primal blockangular structure of the resulting linear optimization problems is exploited by the interiorpoint method, allowing the (either exact or inexact) efficient solution of large instances. The effect of different modeling conditions and problem specifications on the computational performance are also investigated both theoretically and empirically, providing a deeper understanding of the significant factors influencing the overall efficiency of the cuttingplane method. This approach
allowed the solution of instances of up to 200 potential locations, one million customers and three periods, resulting in mixed integer linear optimization problems of up to 600 binary and 600 millions of continuous variables. Those problems were solved by the specialized approach in less than one hour, outperforming other stateof
theart methods, which exhausted the (144 Gigabytes of) available memory in the largest instances.
Thu, 17 Dec 2015 18:28:33 GMT
http://hdl.handle.net/2117/80887
20151217T18:28:33Z
Castro Pérez, Jordi
Nasini, Stefano
Saldanha da Gama, Francisco
We propose a cuttingplane approach (namely, Benders decomposition) for a class of capacitated multiperiod facility location problems. The novelty of this approach lies on the use of a specialized interiorpoint method for solving the Benders subproblems. The primal blockangular structure of the resulting linear optimization problems is exploited by the interiorpoint method, allowing the (either exact or inexact) efficient solution of large instances. The effect of different modeling conditions and problem specifications on the computational performance are also investigated both theoretically and empirically, providing a deeper understanding of the significant factors influencing the overall efficiency of the cuttingplane method. This approach
allowed the solution of instances of up to 200 potential locations, one million customers and three periods, resulting in mixed integer linear optimization problems of up to 600 binary and 600 millions of continuous variables. Those problems were solved by the specialized approach in less than one hour, outperforming other stateof
theart methods, which exhausted the (144 Gigabytes of) available memory in the largest instances.

Calidad 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 GMT
http://hdl.handle.net/2117/79037
20151111T13:37:28Z
Cobo Valeri, Erik
Moher, David
Boutron, Isabelle
González Alastrué, José Antonio

Solutions 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 GMT
http://hdl.handle.net/2117/78990
20151110T18:59:27Z
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.

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 inadvance 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 GMT
http://hdl.handle.net/2117/78886
20151106T11:48:44Z
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 inadvance 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 firststage 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: providerside uncertainty, receiverside uncertainty, uncertainty inbetween, and uncertainty with respect to the cost parameters.; For this novel problem, a sophisticated branchandcut framework based on Benders decomposition is designed and complemented by several nontrivial enhancements, including scenario sorting, dual lifting, branching priorities, matheuristics and zerohalf 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 GMT
http://hdl.handle.net/2117/77975
20151020T12:49:02Z
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 firststage 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: providerside uncertainty, receiverside uncertainty, uncertainty inbetween, and uncertainty with respect to the cost parameters.; For this novel problem, a sophisticated branchandcut framework based on Benders decomposition is designed and complemented by several nontrivial enhancements, including scenario sorting, dual lifting, branching priorities, matheuristics and zerohalf 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.