Articles de revista
http://hdl.handle.net/2117/3321
Mon, 26 Jun 2017 14:01:29 GMT2017-06-26T14:01:29ZTaking advantage of unexpected WebCONSORT results
http://hdl.handle.net/2117/103249
Taking advantage of unexpected WebCONSORT results
Cobo Valeri, Erik; González Alastrué, José Antonio
To estimate treatment effects, trials are initiated by randomising patients to the interventions under study and finish by comparing patient evolution. In order to improve the trial report, the CONSORT statement provides authors and peer reviewers with a guide of the essential items that would allow research replication. Additionally, WebCONSORT aims to facilitate author reporting by providing the items from the different CONSORT extensions that are relevant to the trial being reported. WebCONSORT has been estimated to improve the proportion of reported items by 0.04 (95% CI, –0.02 to 0.10), interpreted as “no important difference”, in accordance with the scheduled desired scenario of a 0.15 effect size improvement. However, in a non-scheduled analysis, it was found that, despite clear instructions, around a third of manuscripts selected for trials by the editorial staff were not actually randomised trials. We argue that surprises benefit science, and that further research should be conducted in order to improve the performance of editorial staff.
Tue, 04 Apr 2017 09:20:35 GMThttp://hdl.handle.net/2117/1032492017-04-04T09:20:35ZCobo Valeri, ErikGonzález Alastrué, José AntonioTo estimate treatment effects, trials are initiated by randomising patients to the interventions under study and finish by comparing patient evolution. In order to improve the trial report, the CONSORT statement provides authors and peer reviewers with a guide of the essential items that would allow research replication. Additionally, WebCONSORT aims to facilitate author reporting by providing the items from the different CONSORT extensions that are relevant to the trial being reported. WebCONSORT has been estimated to improve the proportion of reported items by 0.04 (95% CI, –0.02 to 0.10), interpreted as “no important difference”, in accordance with the scheduled desired scenario of a 0.15 effect size improvement. However, in a non-scheduled analysis, it was found that, despite clear instructions, around a third of manuscripts selected for trials by the editorial staff were not actually randomised trials. We argue that surprises benefit science, and that further research should be conducted in order to improve the performance of editorial staff.Hub network design problems with profits
http://hdl.handle.net/2117/102005
Hub network design problems with profits
Alibeyg, Armaghan; Contreras Aguilar, Ivan; Fernández Aréizaga, Elena
This paper presents a class of hub network design problems with profit-oriented objectives, which extend several families of classical hub location problems. Potential applications arise in the design of air and ground transportation networks. These problems include decisions on the origin/destination nodes that will be served as well as the activation of different types of edges, and consider the simultaneous optimization of the collected profit, setup cost of the hub network and transportation cost. Alternative models and integer programming formulations are proposed and analyzed. Results from computational experiments show the complexity of such models and highlight their superiority for decision-making.
Tue, 07 Mar 2017 09:01:52 GMThttp://hdl.handle.net/2117/1020052017-03-07T09:01:52ZAlibeyg, ArmaghanContreras Aguilar, IvanFernández Aréizaga, ElenaThis paper presents a class of hub network design problems with profit-oriented objectives, which extend several families of classical hub location problems. Potential applications arise in the design of air and ground transportation networks. These problems include decisions on the origin/destination nodes that will be served as well as the activation of different types of edges, and consider the simultaneous optimization of the collected profit, setup cost of the hub network and transportation cost. Alternative models and integer programming formulations are proposed and analyzed. Results from computational experiments show the complexity of such models and highlight their superiority for decision-making.Introducing capacitaties in the location of unreliable facilities
http://hdl.handle.net/2117/100936
Introducing capacitaties in the location of unreliable facilities
Albareda Sambola, Maria; Landete, Mercedes; Monge Ivars, Juan Francisco; Sainz Pardo, José Luis
The goal of this paper is to introduce facility capacities into the Reliability Fixed-Charge Location Problem in a sensible way. To this end, we develop and compare different models, which represent a tradeoff between the extreme models currently available in the literature, where a priori assignments are either fixed, or can be fully modified after failures occur. In a series of computational experiments we analyze the obtained solutions and study the price of introducing capacity constraints according to the alternative models both, in terms of computational burden and of solution cost.
Mon, 13 Feb 2017 15:30:49 GMThttp://hdl.handle.net/2117/1009362017-02-13T15:30:49ZAlbareda Sambola, MariaLandete, MercedesMonge Ivars, Juan FranciscoSainz Pardo, José LuisThe goal of this paper is to introduce facility capacities into the Reliability Fixed-Charge Location Problem in a sensible way. To this end, we develop and compare different models, which represent a tradeoff between the extreme models currently available in the literature, where a priori assignments are either fixed, or can be fully modified after failures occur. In a series of computational experiments we analyze the obtained solutions and study the price of introducing capacity constraints according to the alternative models both, in terms of computational burden and of solution cost.Interior-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.
Thu, 22 Sep 2016 15:31:40 GMThttp://hdl.handle.net/2117/901502016-09-22T15:31:40ZCastro 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.
Thu, 22 Sep 2016 15:07:07 GMThttp://hdl.handle.net/2117/901492016-09-22T15:07:07ZCastro 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.A mathematical programming approach for different scenarios of bilateral bartering
http://hdl.handle.net/2117/85754
A mathematical programming approach for different scenarios of bilateral bartering
Nasini, Stefano; Castro Pérez, Jordi; Fonseca Casas, Pau
The analysis of markets with indivisible goods and fixed exogenous prices has played an important role in economic models, especially in relation to wage rigidity and unemployment. This paper provides a novel mathematical programming based approach to study pure exchange economies where discrete amounts of commodities are exchanged at fixed prices. Barter processes, consisting in sequences of elementary reallocations of couple of commodities among couples of agents, are formalized as local searches converging to equilibrium allocations. A direct application of the analysed processes in the context of computational economics is provided, along with a Java implementation of the described approaches.
Fri, 15 Apr 2016 15:03:14 GMThttp://hdl.handle.net/2117/857542016-04-15T15:03:14ZNasini, StefanoCastro Pérez, JordiFonseca Casas, PauThe analysis of markets with indivisible goods and fixed exogenous prices has played an important role in economic models, especially in relation to wage rigidity and unemployment. This paper provides a novel mathematical programming based approach to study pure exchange economies where discrete amounts of commodities are exchanged at fixed prices. Barter processes, consisting in sequences of elementary reallocations of couple of commodities among couples of agents, are formalized as local searches converging to equilibrium allocations. A direct application of the analysed processes in the context of computational economics is provided, along with a Java implementation of the described approaches.Importancia de la potencia y la hipótesis en el valor p
http://hdl.handle.net/2117/85046
Importancia de la potencia y la hipótesis en el valor p
Cortés Martínez, Jordi; Casals, Martí; Langohr, Klaus; González Alastrué, José Antonio
Los lectores de Medicina Clínica conocen bien la importancia de definir bien el denominador de una proporción para estimar una probabilidad: “No es lo mismo la probabilidad de que un católico sea Papa que la de que un Papa sea católico”. De forma similar, en un diagnóstico, no es lo mismo la probabilidad de que un enfermo dé positivo (sensibilidad), que la de que un caso que ha dado positivo esté enfermo (valor predictivo de un positivo).
El valor p (o valor de p, o p-valor, o simplemente p) guarda cierta analogía con las probabilidades diagnósticas, ya que se define como la probabilidad de obtener un resultado tan significativo o más que el observado —dar positivo en la prueba diagnóstica— asumiendo cierta una hipótesis H: el paciente está sano. No obstante, a un investigador o a un clínico le puede resultar más interesante conocer el valor positivo de una prueba: cuán probable es una hipótesis H —que el paciente esté enfermo— habiendo observado unos resultados extremos.
Fri, 01 Apr 2016 10:51:58 GMThttp://hdl.handle.net/2117/850462016-04-01T10:51:58ZCortés Martínez, JordiCasals, MartíLangohr, KlausGonzález Alastrué, José AntonioLos lectores de Medicina Clínica conocen bien la importancia de definir bien el denominador de una proporción para estimar una probabilidad: “No es lo mismo la probabilidad de que un católico sea Papa que la de que un Papa sea católico”. De forma similar, en un diagnóstico, no es lo mismo la probabilidad de que un enfermo dé positivo (sensibilidad), que la de que un caso que ha dado positivo esté enfermo (valor predictivo de un positivo).
El valor p (o valor de p, o p-valor, o simplemente p) guarda cierta analogía con las probabilidades diagnósticas, ya que se define como la probabilidad de obtener un resultado tan significativo o más que el observado —dar positivo en la prueba diagnóstica— asumiendo cierta una hipótesis H: el paciente está sano. No obstante, a un investigador o a un clínico le puede resultar más interesante conocer el valor positivo de una prueba: cuán probable es una hipótesis H —que el paciente esté enfermo— habiendo observado unos resultados extremos.Scheduling policies for multi-period services
http://hdl.handle.net/2117/84649
Scheduling policies for multi-period services
Núñez del Toro, Alma Cristina; Fernández Aréizaga, Elena; Kalcsics, Jörg; Nickel, Stefan
This paper discusses a multi-period service scheduling problem. In this problem, a set of customers is given who periodically require service over a finite time horizon. To satisfy the service demands, a set of operators is given, each with a fixed capacity in terms of the number of customers an operator can serve per period. The task is to determine for each customer the periods in which he will be visited by an operator such that the periodic service requests of the customers are adhered to and the total number of operators used over the time horizon is minimal. Two alternative policies for scheduling customer visits are considered. In the first one, a customer is visited just on time, i.e., in the period where he or she has a demand for service. The second policy allows service visits ahead of time. The rationale behind this policy is that allowing irregular visits may reduce the overall number of operators needed throughout the time horizon. To solve the problem, integer linear programming formulations are proposed for both policies and numerical experiments are presented that show the reduction in the number of operators used when visits ahead of time are allowed. As only small instances can be solved optimally, a heuristic algorithm is introduced in order to obtain good quality solutions and shorter computing times.
Thu, 17 Mar 2016 15:09:08 GMThttp://hdl.handle.net/2117/846492016-03-17T15:09:08ZNúñez del Toro, Alma CristinaFernández Aréizaga, ElenaKalcsics, JörgNickel, StefanThis paper discusses a multi-period service scheduling problem. In this problem, a set of customers is given who periodically require service over a finite time horizon. To satisfy the service demands, a set of operators is given, each with a fixed capacity in terms of the number of customers an operator can serve per period. The task is to determine for each customer the periods in which he will be visited by an operator such that the periodic service requests of the customers are adhered to and the total number of operators used over the time horizon is minimal. Two alternative policies for scheduling customer visits are considered. In the first one, a customer is visited just on time, i.e., in the period where he or she has a demand for service. The second policy allows service visits ahead of time. The rationale behind this policy is that allowing irregular visits may reduce the overall number of operators needed throughout the time horizon. To solve the problem, integer linear programming formulations are proposed for both policies and numerical experiments are presented that show the reduction in the number of operators used when visits ahead of time are allowed. As only small instances can be solved optimally, a heuristic algorithm is introduced in order to obtain good quality solutions and shorter computing times.Hybrid AC-DC offshore wind power plant topology: optimal design
http://hdl.handle.net/2117/83730
Hybrid AC-DC offshore wind power plant topology: optimal design
Prada Gil, Mikel de; Igualada González, Lucía; Corchero García, Cristina; Gomis Bellmunt, Oriol; Sumper, Andreas
The aim of this paper is to present a hybrid AC-DC offshore wind power plant (OWPP) topology and to optimize its design in order to minimize the OWPP's total cost. This hybrid concept is based on clustering wind turbines and connecting each group to an AC/DC power converter installed on a collector platform which is located between the AC wind turbine array and the HVDC offshore platform. Thereby, individual power converters of each wind turbine are not required, since such AC/DC converters can provide variable speed generator control for each cluster. The optimal design for an OWPP based on the hybrid AC-DC topology is formulated as a MINLP problem. The capital costs of each component within the OWPP as well as the costs associated to the inherent losses of this topology are minimized. The optimal number of AC/DC converters and offshore collector platforms needed, as well as their locations, are determined. The cable route connecting the wind turbines between each other is also optimized. The results suggests a good potential for the hybrid AC-DC OWPP topology achieving a total cost saving of 3.76% for the case study compared to the conventional OWPP topology.
Wed, 02 Mar 2016 18:34:17 GMThttp://hdl.handle.net/2117/837302016-03-02T18:34:17ZPrada Gil, Mikel deIgualada González, LucíaCorchero García, CristinaGomis Bellmunt, OriolSumper, AndreasThe aim of this paper is to present a hybrid AC-DC offshore wind power plant (OWPP) topology and to optimize its design in order to minimize the OWPP's total cost. This hybrid concept is based on clustering wind turbines and connecting each group to an AC/DC power converter installed on a collector platform which is located between the AC wind turbine array and the HVDC offshore platform. Thereby, individual power converters of each wind turbine are not required, since such AC/DC converters can provide variable speed generator control for each cluster. The optimal design for an OWPP based on the hybrid AC-DC topology is formulated as a MINLP problem. The capital costs of each component within the OWPP as well as the costs associated to the inherent losses of this topology are minimized. The optimal number of AC/DC converters and offshore collector platforms needed, as well as their locations, are determined. The cable route connecting the wind turbines between each other is also optimized. The results suggests a good potential for the hybrid AC-DC OWPP topology achieving a total cost saving of 3.76% for the case study compared to the conventional OWPP topology.A novel model for arc territory design: promoting Eulerian districts
http://hdl.handle.net/2117/82920
A novel model for arc territory design: promoting Eulerian districts
Garcia Ayala, Gariela; González Velarde, José Luis; Rios Mercados, Roger; Fernández Aréizaga, Elena
The problem of district design for the implementation of arc routing activities is addressed. The aim is to partition a road network into a given number of sectors to facilitate the organization of the operations to be implemented within the region. This problem arises in numerous applications such as postal delivery, meter readings, winter gritting, road maintenance, and municipal solid waste collection. An integer linear programming model is proposed where a novel set of node parity constraints to favor Eulerian districts is introduced. Series of instances were solved to assess the impact of these parity constraints on the objective function and deadhead distance. Networks with up to 401 nodes and 764 edges were successfully solved. The model is useful at a tactical level as it can be used to promote workload balance, compactness, deadhead distance reduction and parity in districts.
Mon, 15 Feb 2016 12:00:47 GMThttp://hdl.handle.net/2117/829202016-02-15T12:00:47ZGarcia Ayala, GarielaGonzález Velarde, José LuisRios Mercados, RogerFernández Aréizaga, ElenaThe problem of district design for the implementation of arc routing activities is addressed. The aim is to partition a road network into a given number of sectors to facilitate the organization of the operations to be implemented within the region. This problem arises in numerous applications such as postal delivery, meter readings, winter gritting, road maintenance, and municipal solid waste collection. An integer linear programming model is proposed where a novel set of node parity constraints to favor Eulerian districts is introduced. Series of instances were solved to assess the impact of these parity constraints on the objective function and deadhead distance. Networks with up to 401 nodes and 764 edges were successfully solved. The model is useful at a tactical level as it can be used to promote workload balance, compactness, deadhead distance reduction and parity in districts.