Departament d'Estadística i Investigació Operativa
http://hdl.handle.net/2117/3941
2016-09-25T22:36:38ZHerbivores, saprovores and natural enemies respond differently to within-field plant characteristics of wheat fields
http://hdl.handle.net/2117/90156
Herbivores, saprovores and natural enemies respond differently to within-field plant characteristics of wheat fields
Caballero López, Berta; Blanco Moreno, José M.; Pujade Villar, Juli; Ventura, Daniel; Sánchez Espigares, Josep Anton; Sans Serra, Francesc Xavier
Understanding ecosystem functioning in a farmland context by considering the variety of ecological strategies employed by arthropods is a core challenge in ecology and conservation science. We adopted a functional approach in an assessment of the relationship between three functional plant groups (grasses, broad-leaves and legumes) and the arthropod community in winter wheat fields in a Mediterranean dryland context. We sampled the arthropod community as thoroughly as possible with a combination of suction catching and flight-interception trapping. All specimens were identified to the appropriate taxonomic level (family, genus or species) and classified according to their form of feeding: chewing-herbivores, sucking-herbivores, flower-consumers, omnivores, saprovores, parasitoids or predators. We found, a richer plant community favoured a greater diversity of herbivores and, in turn, a richness of herbivores and saprovores enhanced the communities of their natural enemies, which supports the classical trophic structure hypothesis. Grass cover had a positive effect on sucking-herbivores, saprovores and their natural enemies and is probably due to grasses’ ability to provide, either directly or indirectly, alternative resources or simply by offering better environmental conditions. By including legumes in agroecosystems we can improve the conservation of beneficial arthropods like predators or parasitoids, and enhance the provision of ecosystem services such as natural pest control
2016-09-23T10:04:24ZCaballero López, BertaBlanco Moreno, José M.Pujade Villar, JuliVentura, DanielSánchez Espigares, Josep AntonSans Serra, Francesc XavierUnderstanding ecosystem functioning in a farmland context by considering the variety of ecological strategies employed by arthropods is a core challenge in ecology and conservation science. We adopted a functional approach in an assessment of the relationship between three functional plant groups (grasses, broad-leaves and legumes) and the arthropod community in winter wheat fields in a Mediterranean dryland context. We sampled the arthropod community as thoroughly as possible with a combination of suction catching and flight-interception trapping. All specimens were identified to the appropriate taxonomic level (family, genus or species) and classified according to their form of feeding: chewing-herbivores, sucking-herbivores, flower-consumers, omnivores, saprovores, parasitoids or predators. We found, a richer plant community favoured a greater diversity of herbivores and, in turn, a richness of herbivores and saprovores enhanced the communities of their natural enemies, which supports the classical trophic structure hypothesis. Grass cover had a positive effect on sucking-herbivores, saprovores and their natural enemies and is probably due to grasses’ ability to provide, either directly or indirectly, alternative resources or simply by offering better environmental conditions. By including legumes in agroecosystems we can improve the conservation of beneficial arthropods like predators or parasitoids, and enhance the provision of ecosystem services such as natural pest controlInterior-point solver for convex separable block-angular problems
http://hdl.handle.net/2117/90150
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 solves the normal equations using sparse Cholesky factorizations for the block constraints, and a reconditioned 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 as follows: 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 preconditioner). The solver has been hooked to the structure-conveying modelling language (SML) 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 and distances (which are linear and quadratic problems, respectively), and the pseudo-Huber function, a nonlinear approximation to which improves the preconditioner. In the largest instances, of up to 25 millions of variables and 300,000 constraints, this approach is from 2 to 3 orders of magnitude faster than state-of-the-art linear and quadratic optimization solvers.
2016-09-22T15:31:40ZCastro 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 solves the normal equations using sparse Cholesky factorizations for the block constraints, and a reconditioned 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 as follows: 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 preconditioner). The solver has been hooked to the structure-conveying modelling language (SML) 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 and distances (which are linear and quadratic problems, respectively), and the pseudo-Huber function, a nonlinear approximation to which improves the preconditioner. In the largest instances, of up to 25 millions of variables and 300,000 constraints, this approach is from 2 to 3 orders of magnitude faster than state-of-the-art linear and quadratic optimization solvers.A cutting-plane approach for large-scale capacitated multi-period facility location using a specialized interior-point method
http://hdl.handle.net/2117/90149
A cutting-plane approach for large-scale capacitated multi-period facility location using a specialized interior-point method
Castro Pérez, Jordi; Nasini, Stefano; Saldanha da Gama, Francisco
We propose a cutting-plane approach (namely, Benders decomposition) for a class of capacitated multi-period facility location problems. The novelty of this approach lies on the use of a specialized interior-point method for solving the Benders subproblems. The primal block-angular structure of the resulting linear optimization
problems is exploited by the interior-point method, allowing the (either exact or inexact) efficient solution of large instances. The consequences 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 cutting-plane method.
The methodology proposed 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 and a half, outperforming other state-of-the-art methods, which exhausted the (144 Gigabytes of) available memory in the largest instances.
2016-09-22T15:07:07ZCastro Pérez, JordiNasini, StefanoSaldanha da Gama, FranciscoWe propose a cutting-plane approach (namely, Benders decomposition) for a class of capacitated multi-period facility location problems. The novelty of this approach lies on the use of a specialized interior-point method for solving the Benders subproblems. The primal block-angular structure of the resulting linear optimization
problems is exploited by the interior-point method, allowing the (either exact or inexact) efficient solution of large instances. The consequences 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 cutting-plane method.
The methodology proposed 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 and a half, outperforming other state-of-the-art methods, which exhausted the (144 Gigabytes of) available memory in the largest instances.Automatic incident detection and estimation of incident probabilities for incident management purposes. a case study in barcelona
http://hdl.handle.net/2117/89677
Automatic incident detection and estimation of incident probabilities for incident management purposes. a case study in barcelona
Barceló Bugeda, Jaime; Montero Mercadé, Lídia; Perarnau, Josep
Real-time models for automatic Incident Detection and Estimation of Incident Probabilities contribute to the improvement of the effectiveness of incident management policies devoted to increase road safety. New, advanced-technology hardware and software, and new models make possible the improved monitoring, surveillance and management of high-risk road locations in urban and rural areas of the European Union (10). Fast and reliable detection and prediction models for incidents, imbedded in traffic management environments, is instrumental in the development of control strategies to reduce traffic delay and the likelihood of new incidents before they occur.
2016-09-07T14:36:29ZBarceló Bugeda, JaimeMontero Mercadé, LídiaPerarnau, JosepReal-time models for automatic Incident Detection and Estimation of Incident Probabilities contribute to the improvement of the effectiveness of incident management policies devoted to increase road safety. New, advanced-technology hardware and software, and new models make possible the improved monitoring, surveillance and management of high-risk road locations in urban and rural areas of the European Union (10). Fast and reliable detection and prediction models for incidents, imbedded in traffic management environments, is instrumental in the development of control strategies to reduce traffic delay and the likelihood of new incidents before they occur.A unified approach to authorship attribution and verification
http://hdl.handle.net/2117/89602
A unified approach to authorship attribution and verification
Puig Oriol, Xavier; Font Valverde, Martí; Ginebra Molins, Josep
In authorship attribution, one assigns texts from an unknown author to either one of two or more candidate authors by comparing the disputed texts with texts known to have been written by the candidate authors. In authorship verification, one decides whether a text or a set of texts could have been written by a given author. These two problems are usually treated separately. By assuming an open-set classification framework for the attribution problem, contemplating the possibility that none of the candidate authors is the unknown author, the verification problem becomes a special case of attribution problem. Here both problems are posed as a formal Bayesian multinomial model selection problem and are given a closed-form solution, tailored for categorical data, naturally incorporating text length and dependence in the analysis, and coping well with settings with a small number of training texts. The approach to authorship verification is illustrated by exploring whether a court ruling sentence could have been written by the judge that signs it, and the approach to authorship attribution is illustrated by revisiting the authorship attribution of the Federalist papers and through a small simulation study.
2016-09-06T10:09:51ZPuig Oriol, XavierFont Valverde, MartíGinebra Molins, JosepIn authorship attribution, one assigns texts from an unknown author to either one of two or more candidate authors by comparing the disputed texts with texts known to have been written by the candidate authors. In authorship verification, one decides whether a text or a set of texts could have been written by a given author. These two problems are usually treated separately. By assuming an open-set classification framework for the attribution problem, contemplating the possibility that none of the candidate authors is the unknown author, the verification problem becomes a special case of attribution problem. Here both problems are posed as a formal Bayesian multinomial model selection problem and are given a closed-form solution, tailored for categorical data, naturally incorporating text length and dependence in the analysis, and coping well with settings with a small number of training texts. The approach to authorship verification is illustrated by exploring whether a court ruling sentence could have been written by the judge that signs it, and the approach to authorship attribution is illustrated by revisiting the authorship attribution of the Federalist papers and through a small simulation study.A methodology for private transportation planning assessment: GETRAM environment, an application to Barcelona's metropolitan area
http://hdl.handle.net/2117/89579
A methodology for private transportation planning assessment: GETRAM environment, an application to Barcelona's metropolitan area
Montero Mercadé, Lídia; Codina Sancho, Esteve; Barceló Bugeda, Jaime; Barceló, P
Traffic assignment models based on the user equilibrium approach are one of the most widely used tools in transportation planning analysis. Based on Wardrop’s, principle as a behavioral principle modeling the route choice process, they lead to a nice mathematical model for which there are efficient algorithms that provide solutions in terms of the expected flows on network links. Resulting flows offer a static average view of the expected use of the road infrastructure under the modeling hypothesis. This information has usually been enough for the planning decisions. However, the evolution of advanced technologies and their application to modern traffic management systems require in most cases a dynamic view complementing the static estimates provided by the assignment tools. The planned infrastructure is probably sufficient for average demand, but time-varying traffic flows, i.e. at peak periods, combined with the influence of road geometry, can produce undesired congestion that can not be forecasted or analysed with the static tools. There is a clear case for a change in the analysis methodology such as combination of a well known traffic assignment tool, the EMME/2 model, with a microscopic traffic simulator, the AIMSUN2 (Advanced Interactive Microscopic Simulator for Urban and Non-urban Networks) which this paper proposes.
2016-09-05T12:13:01ZMontero Mercadé, LídiaCodina Sancho, EsteveBarceló Bugeda, JaimeBarceló, PTraffic assignment models based on the user equilibrium approach are one of the most widely used tools in transportation planning analysis. Based on Wardrop’s, principle as a behavioral principle modeling the route choice process, they lead to a nice mathematical model for which there are efficient algorithms that provide solutions in terms of the expected flows on network links. Resulting flows offer a static average view of the expected use of the road infrastructure under the modeling hypothesis. This information has usually been enough for the planning decisions. However, the evolution of advanced technologies and their application to modern traffic management systems require in most cases a dynamic view complementing the static estimates provided by the assignment tools. The planned infrastructure is probably sufficient for average demand, but time-varying traffic flows, i.e. at peak periods, combined with the influence of road geometry, can produce undesired congestion that can not be forecasted or analysed with the static tools. There is a clear case for a change in the analysis methodology such as combination of a well known traffic assignment tool, the EMME/2 model, with a microscopic traffic simulator, the AIMSUN2 (Advanced Interactive Microscopic Simulator for Urban and Non-urban Networks) which this paper proposes.The general traffic assignment problem: a proximal point method for equilibrium computation with applications to the demand adjustment problem
http://hdl.handle.net/2117/89501
The general traffic assignment problem: a proximal point method for equilibrium computation with applications to the demand adjustment problem
Montero Mercadé, Lídia; Codina Sancho, Esteve
An adaptation of the proximal algorithm for the traffic assignment problem under a user equilibrium formulation for a general asymmetric traffic network is presented in
this paper. It follows the recently published results of Pennanen regarding convergence under non monotonicity. As it is well known the problem can be formulated as
a variational inequality and the algorithmic solutions developed up to date guarantee convergence only under too restrictive conditions which are difficult to appear in practice.
In this paper it is also discussed the possibility of including the algorithm on a demand adjustment problem formulated as a bilevel program with lower level traffic
equilibrium constraints expressed as a variational inequality.
2016-09-02T13:07:07ZMontero Mercadé, LídiaCodina Sancho, EsteveAn adaptation of the proximal algorithm for the traffic assignment problem under a user equilibrium formulation for a general asymmetric traffic network is presented in
this paper. It follows the recently published results of Pennanen regarding convergence under non monotonicity. As it is well known the problem can be formulated as
a variational inequality and the algorithmic solutions developed up to date guarantee convergence only under too restrictive conditions which are difficult to appear in practice.
In this paper it is also discussed the possibility of including the algorithm on a demand adjustment problem formulated as a bilevel program with lower level traffic
equilibrium constraints expressed as a variational inequality.Numerical implementation and computational results of nonlinear network optimization with linear side constraints
http://hdl.handle.net/2117/89385
Numerical implementation and computational results of nonlinear network optimization with linear side constraints
Heredia, F.-Javier (Francisco Javier); Nabona Francisco, Narcís
2016-08-25T13:03:53ZHeredia, F.-Javier (Francisco Javier)Nabona Francisco, NarcísOptimal location of fast charging stations in Barcelona: a flow-capturing approach
http://hdl.handle.net/2117/89381
Optimal location of fast charging stations in Barcelona: a flow-capturing approach
Cruz Zambrano, Miguel; Corchero García, Cristina; Igualada González, Lucía; Bernardo, Valeria
The aim of this paper is to find the optimal location of electric vehicle (EV) fast charging stations by means of two methodologies: a classical flow-capturing optimization model involving only mobility needs, and an advanced flow-capturing optimization model including distribution network and location costs. While the first model aims to maximize the public service provided by the fast charging stations, the second also considers the incurred cost for providing it. Results from both models are compared in order to analyse the effect of both planning approaches in total cost of installation. As a case study it has been chosen the city of Barcelona.
2016-08-24T08:57:52ZCruz Zambrano, MiguelCorchero García, CristinaIgualada González, LucíaBernardo, ValeriaThe aim of this paper is to find the optimal location of electric vehicle (EV) fast charging stations by means of two methodologies: a classical flow-capturing optimization model involving only mobility needs, and an advanced flow-capturing optimization model including distribution network and location costs. While the first model aims to maximize the public service provided by the fast charging stations, the second also considers the incurred cost for providing it. Results from both models are compared in order to analyse the effect of both planning approaches in total cost of installation. As a case study it has been chosen the city of Barcelona.A bilevel programming formulation for modelling the location of information: points for traffic conditions
http://hdl.handle.net/2117/89379
A bilevel programming formulation for modelling the location of information: points for traffic conditions
Montero Mercadé, Lídia; Codina Sancho, Esteve; Marín, Angel
2016-08-23T11:36:25ZMontero Mercadé, LídiaCodina Sancho, EsteveMarín, Angel