Artículos (Estadística e Investigación Operativa)

URI permanente para esta colecciónhttps://hdl.handle.net/11441/10844

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Mostrando 1 - 20 de 409

E-commerce shipping through a third-party supply chain
(Elsevier, 2020-05-09) Ponce López, Diego; Contreras, Iván; Laporte, Gilbert; Universidad de Sevilla. Departamento de Estadística e Investigación Operativa; Universidad de Sevilla. FQM331: Métodos y Modelos de la Estadística y la Investigación Operativa
We consider an e-commerce retailer who must ship orders from a warehouse to a set of customers with delivery deadlines. As is often the case, the retailer uses a third-party service provider to ensure its distribution. The retailer can enter the supply chain of the service provider at various levels. Entering it at a higher level entails lower sorting costs for the retailer, but higher delivery costs, and longer delivery times. The customer orders arrive at various moments over a rolling planning horizon. This means that the retailer must also make consolidation decisions. We model and solve the static and dynamic cases of this problem. The static case is modeled as an integer linear program and solved by CPLEX. We develop and compare four shipping policies for the dynamic case. Extensive computational results based on real location data from California and Texas are reported.
Portfolio problems with two levels decision-makers: Optimal portfolio selection with pricing decisions on transaction costs
(Elsevier, 2019-12-26) Leal Palazón, Marina; Ponce López, Diego; Puerto Albandoz, Justo; Universidad de Sevilla. Departamento de Estadística e Investigación Operativa; Universidad de Sevilla. FQM331: Métodos y Modelos de la Estadística y la Investigación Operativa
This paper presents novel bilevel leader-follower portfolio selection problems in which the financial intermediary becomes a decision-maker. This financial intermediary decides on the unit transaction costs for investing in some securities, maximizing its benefits, and the investor chooses his optimal portfolio, minimizing risk and ensuring a given expected return. Hence, transaction costs become decision variables in the portfolio problem, and two levels of decision-makers are incorporated: the financial intermediary and the investor. These situations give rise to general Nonlinear Programming formulations in both levels of the decision process. We present different bilevel versions of the problem: financial intermediary-leader, investor-leader, and social welfare; besides, their properties are analyzed. Moreover, we develop Mixed Integer Linear Programming formulations for some of the proposed problems and effective algorithms for some others. Finally, we report on some computational experiments performed on data taken from the Dow Jones Industrial Average, and analyze and compare the results obtained by the different models.
Continuous location under the effect of ‘refraction’
(Springer, 2016-03-08) Blanco, Víctor; Puerto Albandoz, Justo; Ponce López, Diego; Universidad de Sevilla. Departamento de Estadística e Investigación Operativa; Universidad de Sevilla. FQM331: Métodos y Modelos de la Estadística y la Investigación Operativa
In this paper we address the problem of locating a new facility on a d-dimensional space when the distance measure (- or polyhedral-norms) is different at each one of the sides of a given hyperplane. We relate this problem with the physical phenomenon of refraction, and extend it to any finite dimensional space and different distances at each one of the sides of any hyperplane. An application to this problem is the location of a facility within or outside an urban area where different distance measures must be used. We provide a new second order cone programming formulation, based on the -norm representation given in Blanco et al. (Comput Optim Appl 58(3):563–595, 2014) that allows to solve the problem in any finite dimensional space with second order cone or semidefinite programming tools. We also extend the problem to the case where the hyperplane is considered as a rapid transit media (a different third norm is also considered over ) that allows the demand to travel, whenever it is convenient, through to reach the new facility. Extensive computational experiments run in Gurobi are reported in order to show the effectiveness of the approach. Some extensions of these models are also presented.
A comparative study of formulations and solution methods for the discrete ordered p-median problem
(Elsevier, 2016-06-06) Labbé, Martine; Ponce López, Diego; Puerto Albandoz, Justo; Universidad de Sevilla. Departamento de Estadística e Investigación Operativa; Universidad de Sevilla. FQM331: Métodos y Modelos de la Estadística y la Investigación Operativa
This paper presents several new formulations for the Discrete Ordered Median Problem (DOMP) based on its similarity with some scheduling problems. Some of the new formulations present a considerably smaller number of constraints to define the problem with respect to some previously known formulations. Furthermore, the lower bounds provided by their linear relaxations improve the ones obtained with previous formulations in the literature even when strengthening is not applied. We also present a polyhedral study of the assignment polytope of our tightest formulation showing its proximity to the convex hull of the integer solutions of the problem. Several resolution approaches, among which we mention a branch and cut algorithm, are compared. Extensive computational results on two families of instances, namely randomly generated and from Beasley's OR-library, show the power of our methods for solving DOMP.
A fresh view on the Discrete Ordered Median Problem based on partial monotonicity
(Elsevier, 2020-04-14) Marín, Alfredo; Ponce López, Diego; Puerto Albandoz, Justo; Universidad de Sevilla. Departamento de Estadística e Investigación Operativa; Universidad de Sevilla. FQM331: Métodos y Modelos de la Estadística y la Investigación Operativa
This paper presents new results for the Discrete Ordered Median Problem (DOMP). It exploits properties of k-sum optimization to derive specific formulations for the monotone DOMP (MDOMP), that arises when the λ weights are non-decreasing monotone, and new formulations for the general non-monotone DOMP. The main idea in our approach is to express ordered weighted averages as telescopic sums whose terms are k-sums, with positive and negative coefficients. Formulations of k-sums with positive coefficients derive from the linear programming representations obtained by Ogryczack and Tamir (2003) and Blanco, Ali, and Puerto (2014). Valid formulations for k-sums with negative coefficients are more elaborated and we present 4 different approaches, all of them based on mixed integer programming formulations. An extensive computational experience based on a collection of well-known instances shows the usefulness of the new formulations to solve difficult problems such as trimmed and anti-trimmed mean.
Identification problem in plug-flow chemical reactors using the adjoint method
(Elsevier, 2016-11-25) Bermúdez, A.; Esteben, N.; Ferrín, J.L.; Rodríguez Calo, J.F.; Sillero Denamiel, María Remedios; Universidad de Sevilla. Departamento de Estadística e Investigación Operativa; Universidad de Sevilla. FQM329 Optimización
The aim of this work is to solve identification problems in plug-flow chemical reactors. For this purpose an adjoint-based algorithm for parameter identification problems in systems of partial differential equations is presented. The adjoint method allows us to calculate the gradient of the objective function and the constraint functions with respect to the unknown parameters significantly reducing the computer time. This leads to solve a minimization problem, in which an objective function is defined in order to quantify the mismatch between the observed data and the numerical solution of the parameterized chemical model. For solving the initial and boundary-value problem we use finite-difference schemes. More precisely, we propose a second-order BDF method initialized with a first-order one. The algorithm proposed was implemented in a computer program and some numerical results are shown. The efficiency of the adjoint method, compared with the classical formula of incremental quotients, is also presented.
On sparse ensemble methods: An application to short-term predictions of the evolution of COVID-19
(Elsevier, 2021-12-01) Benítez Peña, Sandra; Carrizosa Priego, Emilio José; Guerrero, Vanesa; Jiménez Gamero, María Dolores; Martín Barragán, Belén; Molero Río, Cristina; Ramírez Cobo, Josefa; Romero Morales, María Dolores; Sillero Denamiel, María Remedios; Universidad de Sevilla. Departamento de Estadística e Investigación Operativa; Universidad de Sevilla. FQM329 Optimización
Since the seminal paper by Bates and Granger in 1969, a vast number of ensemble methods that combine different base regressors to generate a unique one have been proposed in the literature. The so-obtained regressor method may have better accuracy than its components, but at the same time it may overfit, it may be distorted by base regressors with low accuracy, and it may be too complex to understand and explain. This paper proposes and studies a novel Mathematical Optimization model to build a sparse ensemble, which trades off the accuracy of the ensemble and the number of base regressors used. The latter is controlled by means of a regularization term that penalizes regressors with a poor individual performance. Our approach is flexible to incorporate desirable properties one may have on the ensemble, such as controlling the performance of the ensemble in critical groups of records, or the costs associated with the base regressors involved in the ensemble. We illustrate our approach with real data sets arising in the COVID-19 context.
Bayesian Influence Diagnostics in Radiocarbon Dating
(Taylor & Francis, 2012-08-27) Fernández Ponce, José María; Palacios Rodríguez, Fátima; Rodríguez Griñolo, María del Rosario; Universidad de Sevilla. Departamento de Estadística e Investigación Operativa; Universidad de Sevilla. FQM328. Métodos cuantitativos en evaluación
Linear models constitute the primary statistical technique for any experimental science. A major topic in this area is the detection of influential subsets of data, that is, of observations that are influential in terms of their effect on the estimation of parameters in linear regression or of the total population parameters. Numerous studies exist on radiocarbon dating which propose a value consensus and remove possible outliers after the corresponding testing. An influence analysis for the value consensus from a Bayesian perspective is developed in this article.
Generalized Pareto processes for simulating space-time extreme events: an application to precipitation reanalyses
(Springer, 2020-10-03) Palacios Rodríguez, Fátima; Toulemonde, G.; Carreau, J.; Opitz, T.; Universidad de Sevilla. Departamento de Estadística e Investigación Operativa; Universidad de Sevilla. FQM328. Métodos cuantitativos en evaluación
To better manage the risks of destructive natural disasters, impact models can be fed with simulations of extreme scenarios to study the sensitivity to temporal and spatial variability. We propose a semi-parametric stochastic framework that enables simulations of realistic spatio-temporal extreme fields using a moderate number of observed extreme space-time episodes to generate an unlimited number of extreme scenarios of any magnitude. Our framework draws sound theoretical justification from extreme value theory, building on generalized Pareto limit processes arising as limits for event magnitudes exceeding a high threshold. Specifically, we exploit asymptotic stability properties by decomposing extreme event episodes into a scalar magnitude variable (that is resampled), and an empirical profile process representing space-time variability. For illustration on hourly gridded precipitation data in Mediterranean France, we calculate various risk measures using extreme event simulations for yet unobserved magnitudes, and we highlight contrasted behavior for different definitions of the magnitude variable.
On multivariate extensions of the conditional Value-at-Risk measure
(Elsevier, 2015-03-12) Di Bernardino, Elena; Fernández Ponce, E.; Palacios Rodríguez, Fátima; Rodríguez Griñolo, María del Rosario; Universidad de Sevilla. Departamento de Estadística e Investigación Operativa; Universidad de Sevilla. FQM328. Métodos cuantitativos en evaluación
CoVaR is a systemic risk measure proposed by Adrian and Brunnermeier (2011) able to measure a financial institution’s contribution to systemic risk and its contribution to the risk of other financial institutions. CoVaR stands for conditional Value-at-Risk, i.e. it indicates the Value at Risk for a financial institution that is conditional on a certain scenario. In this paper, two alternative extensions of the classic univariate Conditional Value-at-Risk are introduced in a multivariate setting. The two proposed multivariate CoVaRs are constructed from level sets of multivariate distribution functions (resp. of multivariate survival distribution functions). These vector-valued measures have the same dimension as the underlying risk portfolio. Several characterizations of these new risk measures are provided in terms of the copula structure and stochastic orderings of the marginal distributions. Interestingly, these results are consistent with existing properties on univariate risk measures. Furthermore, comparisons between existent risk measures and the proposed multivariate CoVaR are developed. Illustrations are given in the class of Archimedean copulas. Estimation procedure for the multivariate proposed CoVaRs is illustrated in simulated studies and insurance real data.
Estimation of extreme quantiles conditioning on multivariate critical layers
(Wiley, 2016-02-08) Di Bernardino, Elena; Palacios Rodríguez, Fátima; Universidad de Sevilla. Departamento de Estadística e Investigación Operativa; Universidad de Sevilla. FQM328. Métodos cuantitativos en evaluación
Let Ti:=[Xi|X∈∂L(α)], for i = 1,…,d, where X = (X1,…,Xd) is a risk vector and ∂L(α) is the associated multivariate critical layer at level α∈(0,1). The aim of this work is to propose a non-parametric extreme estimation procedure for the (1 − pn)-quantile of Ti for a fixed α and when pn→0, as the sample size n→+∞. An extrapolation method is developed under the Archimedean copula assumption for the dependence structure of X and the von Mises condition for marginal Xi. The main result is the central limit theorem for our estimator for p = pn→0, when n tends towards infinity. A set of simulations illustrates the finite-sample performance of the proposed estimator. We finally illustrate how the proposed estimation procedure can help in the evaluation of extreme multivariate hydrological risks. Copyright © 2016 John Wiley & Sons, Ltd.
Estimation of extreme Component-wise Excess design realization: a hydrological application
(Springer, 2017-02-09) Di Bernardino, Elena; Palacios Rodríguez, Fátima; Universidad de Sevilla. Departamento de Estadística e Investigación Operativa; Universidad de Sevilla. FQM328. Métodos cuantitativos en evaluación
The classic univariate risk measure in environmental sciences is the Return Period (RP). The RP is traditionally defined as “the average time elapsing between two successive realizations of a prescribed event”. The notion of design quantile related with RP is also of great importance. The design quantile represents the “value of the variable(s) characterizing the event associated with a given RP”. Since an individual risk may strongly be affected by the degree of dependence amongst all risks, the need for the provision of multivariate design quantiles has gained ground. In contrast to the univariate case, the design quantile definition in the multivariate setting presents certain difficulties. In particular, Salvadori, G., De Michele, C. and Durante F. define in the paper called “On the return period and design in a multivariate framework” (Hydrol Earth Syst Sci 15:3293–3305, 2011) the design realization as the vector that maximizes a weight function given that the risk vector belongs to a given critical layer of its joint multivariate distribution function. In this paper, we provide the explicit expression of the aforementioned multivariate risk measure in the Archimedean copula setting. Furthermore, this measure is estimated by using Extreme Value Theory techniques and the asymptotic normality of the proposed estimator is studied. The performance of our estimator is evaluated on simulated data. We conclude with an application on a real hydrological data-set.
Smooth copula-based generalized extreme value model and spatial interpolation for extreme rainfall in Central Eastern Canada
(Wiley, 2023-02-11) Palacios Rodríguez, Fátima; Di Bernardino, Elena; Maihot, Melina; Universidad de Sevilla. Departamento de Estadística e Investigación Operativa
This paper proposes a smooth copula-based Generalized Extreme Value (GEV) model to map and predict extreme rainfall in Central Eastern Canada. The considered data contains a large portion of missing values, and one observes several nonconcomitant record periods at different stations. The proposed two-step approach combines GEV parameters' smooth functions in space through the use of spatial covariates and a flexible hierarchical copula-based model to take into account dependence between the recording stations. The hierarchical copula structure is detected via a clustering algorithm implemented with an adapted version of the copula-based dissimilarity measure recently introduced in the literature. Finally, we compare the classical GEV parameter interpolation approaches with the proposed smooth copula-based GEV modeling approach.
On the exact reproduction number in SIS epidemic models with vertical transmission
(Springer, 2023-08-22) Gómez Corral, A.; Palacios Rodríguez, Fátima; Rodríguez Bernal, M.T.; Universidad de Sevilla. Departamento de Estadística e Investigación Operativa
This paper proposes a bi-variate competition process to describe the spread of epidemics of SIS type through both horizontal and vertical transmission. The interest is in the exact reproduction number, , which is seen to be the stochastic version of the well-known basic reproduction number. We characterize the probability distribution function of by decomposing this number into two random contributions allowing us to distinguish between infectious person-to-person contacts and infections of newborns with infective parents. Numerical examples are presented to illustrate our analytical results.
A Markov chain model to investigate the spread of antibiotic-resistant bacteria in hospitals
(Wiley, 2023-08-31) Chalub, Fabio A.C.C.; Gómez Corral, Antonio; López García, Martín; Palacios Rodríguez, Fátima; Universidad de Sevilla. Departamento de Estadística e Investigación Operativa
Ordinary differential equation models used in mathematical epidemiology assume explicitly or implicitly large populations. For the study of infections in a hospital, this is an extremely restrictive assumption as typically a hospital ward has a few dozen, or even fewer, patients. This work reframes a well-known model used in the study of the spread of antibiotic-resistant bacteria in hospitals, to consider the pathogen transmission dynamics in small populations. In this vein, this paper proposes a Markov chain model to describe the spread of a single bacterial species in a hospital ward where patients may be free of bacteria or may carry bacterial strains that are either sensitive or resistant to antimicrobial agents. We determine the probability law of the exact reproduction number , which is here defined as the random number of secondary infections generated by those patients who are accommodated in a predetermined bed before a patient who is free of bacteria is accommodated in this bed for the first time. Specifically, we decompose the exact reproduction number into two contributions allowing us to distinguish between infections due to the sensitive and the resistant bacterial strains. Our methodology is mainly based on structured Markov chains and the use of related matrix-analytic methods. This guarantees the compatibility of the new, finite-population model, with large population models present in the literature and takes full advantage, in its mathematical analysis, of the intrinsic stochasticity.
The effect of axial spondyloarthritis on mental health: Results from the Atlas
(The Journal of Rheumatology Publishing Co. Ltd., 2019) Garrido Cumbrera, Marco; Delgado Domínguez, Carlos Jesús; Gálvez Ruiz, David; Blanch Mur, Carles; Navarro Compán, Victoria; Universidad de Sevilla. Departamento de Estadística e Investigación Operativa; Universidad de Sevilla. Departamento de Geografía Física y Análisis Geográfico Regional; Universidad de Sevilla. HUM981: Health & Territory Research; Universidad de Sevilla. FQM328: Métodos cuantitativos en evaluación
Objective: To assess the risk for mental disorders in patients with axSpA and to examine the associated factors with this. Method: In 2016, a sample of 680 axSpA patients was interviewed as part of the development process for the Atlas of Axial Spondyloarthritis in Spain. The risk of mental disorders in these patients was assessed using the General Health Questionnaire (GHQ-12) scale. Additionally, the variables associated with the risk of mental disorders were investigated, including: sociodemographic characteristics (age, gender, relationship, association membership, job status, and educational level); disease status (BASDAI, spinal stiffness and functional limitation); and previous diagnosis of mental disorders (depression and anxiety). Bivariate correlation analyses were performed, followed by multiple hierarchical and stepwise regression analysis. Results: A total of 45.6% patients were at risk of mental disorders. All variables except educational level and thoracic stiffness significantly correlated with risk of mental disorder. Nevertheless, disease activity, functional limitation, and age showed the highest coefficient (r=0.543, p<0.001; r=0.378, p<0.001; r=-0.174, p<0.001, respectively). In the stepwise regression analysis, four variables (disease activity, functional limitation, association membership, and cervical stiffness) explained the majority of the variance for the risk of mental disorders. Disease activity displayed the highest explanatory degree (R2=0.875, p<0.001). Conclusions: In patients with axSpA, the prevalence of risk for mental disorders is high. Combined with a certain sociodemographic profile, high disease activity is a good indicator of the risk of for mental disorders.
Can the Mode and Time of Commuting to Work Affect Mental Health?
(Elsevier, 2021) Garrido Cumbrera, Marco; Braçe, Olta; Gálvez Ruiz, David; López Lara, Enrique Javier; Correa Fernández, José; Universidad de Sevilla. Departamento de Geografía Física y Análisis Geográfico Regional; Universidad de Sevilla. Departamento de Geografía Humana; Universidad de Sevilla. Departamento de Estadística e Investigación Operativa; Universidad de Sevilla. HUM981: Health & Territory Research
Background: Commuting to work is an important part of many people's daily life, with travel times increasing steadily and becoming a growing problem. Longer commutes, increased costs, and certain forms of transport can lead to increased stress and poor psychological health. The aim of the present study is to assess the possible associations between commuting patterns and poor mental health in workers. Methods: This is a cross-sectional study analysing information from the representative population survey 2015 ‘Commuting, Daily Habits and Urban Health’ survey in Mairena del Aljarafe (Spain). For the present study, 294 workers aged from 16–64 years old were included. To detect poor mental health, the 12-item General Health Questionnaire (GHQ-12) was administered. The study also included sociodemographic, lifestyle, and commuting patterns. Associations were tested using Mann-Whitney and Chi-square tests. Pearson's correlation was used to evaluate each item of the GHQ-12 scale. Multiple linear regression was applied to explore factors associated with poor mental health. Results: Of the sample of workers, the mean age was 43.1 years old, 46.6% female, 49.0% had undertaken university study, 38.4% smoked, and 44.5% were overweight/obese. For their commute, 77.1% used a private motor vehicle (vs. 6.9% public transport and 16.0% active transport), allocated 51.9 min/day (54.8 min/day private, 44.2 min/day public, and 39.3 min/day active transport, p=0.004), and spent €91.9/month (€99.7/month private, €59.0/month public, and €59.5/month active transport, p<0.001). Workers who used their private motor vehicle to commute to work presented, as driving time increased, poorer mental health and reported worrying levels of sleep loss, being under stress, and feeling unhappy or depressed. However, for public or active commuters, we cannot reach any of these conclusions. The multiple linear regression model shows that workers who use their private motorised transport and those who spent longer on their commutes were associated with poorer mental health. Conclusions: Our findings show that both driving a motor vehicle and longer commutes are associated with poorer mental health. Therefore, the use of public and active commuting should be encouraged, as well as better management to improve traffic congestion and thus reduce driving times.
Testing Poissonity of a large number of populations
(Springer, 2023-09-29) Jiménez Gamero, María Dolores; Uña Álvarez, J. de; Universidad de Sevilla. Departamento de Estadística e Investigación Operativa; Universidad de Sevilla. FQM153: Estadística e Investigación Operativa
This paper studies the problem of simultaneously testing that each of k samples, coming from k count variables, were all generated by Poisson laws. The means of those populations may differ. The proposed procedure is designed for large k, which can be bigger than the sample sizes. First, a test is proposed for the case of independent samples, and then the obtained results are extended to dependent data. In each case, the asymptotic distribution of the test statistic is stated under the null hypothesis as well as under alternatives, which allows to study the consistency of the test. Specifically, it is shown that the test statistic is asymptotically free distributed under the null hypothesis. The finite sample performance of the test is studied via simulation. A real data set application is included.
Testing normality of a large number of populations
(Springer, 2023-02-12) Jiménez Gamero, María Dolores; Universidad de Sevilla. Departamento de Estadística e Investigación Operativa; Universidad de Sevilla. FQM153: Estadística e Investigación Operativa
This paper studies the problem of simultaneously testing that each of k independent samples come from a normal population. The means and variances of those populations may differ. The proposed procedures are based on the BHEP test and they allow k to increase, which can be even larger than the sample sizes.
Testing for proportions when data are classified into a large number of groups
(Elsevier, 2024-05-11) Alba Fernández, María Virtudes; Jiménez Gamero, María Dolores; Jiménez Jiménez, F.; Universidad de Sevilla. Departamento de Estadística e Investigación Operativa; Universidad de Sevilla. FQM153: Estadística e Investigación Operativa
When dealing with categorical data, a common concern is to check if the observed relative frequencies agree with a certain fixed vector of ideal proportions. Suppose that the population is divided into subpopulations or groups. In such a case, the ideal proportions could vary among groups and one may be interested in simultaneously testing if the observed proportions agree with those ideal proportions in all groups. A novel procedure is proposed for carrying out such a testing problem. The test statistic is shown to be asymptotically normal, avoiding the use of complicated resampling methods to get -values. The asymptotic behavior of the test under alternatives is also studied. Here, by asymptotic, we mean when the number of groups increases; the sample sizes of the data from each group can either stay bounded or grow with the number of groups. The finite sample performance of the new test is empirically evaluated through an extensive simulation study. The usefulness of the proposal is illustrated with some data sets.

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