Sort-Statistics and Operations Research Transactions最新文献

Green hybrid fleets using electric vehicles: solving the heterogeneous vehicle routing problem with multiple driving ranges and loading capacities 使用电动汽车的绿色混合动力车队:解决多行驶里程和多载重能力的异构车辆路径问题

IF 1.6 4区数学

Sort-Statistics and Operations Research Transactions Pub Date : 2020-06-01 DOI: 10.2436/20.8080.02.98

Sara Hatami, M. Eskandarpour, M. Serrano, Ángel Alejandro Juan Pérez, D. Ouelhadj

{"title":"Green hybrid fleets using electric vehicles: solving the heterogeneous vehicle routing problem with multiple driving ranges and loading capacities","authors":"Sara Hatami, M. Eskandarpour, M. Serrano, Ángel Alejandro Juan Pérez, D. Ouelhadj","doi":"10.2436/20.8080.02.98","DOIUrl":"https://doi.org/10.2436/20.8080.02.98","url":null,"abstract":"The introduction of Electric Vehicles (EVs) in modern fleets facilitates green road transportation. However, the driving ranges of EVs are limited by the duration of their batteries, which arise new operational challenges. Hybrid fleets of gas and EVs might be heterogeneous both in loading capacities as well as in driving-range capabilities,whichmakes the design of efficient routing plans a difficult task. In this paper, we propose a newMulti-Round IteratedGreedy (MRIG) metaheuristic to solve the Heterogeneous Vehicle Routing Problem with Multiple Driving ranges and loading capacities (HeVRPMD). MRIG uses a successive approximations method to offer the decision maker a set of alternative fleet configurations,with different distance-based costs and green levels. The numerical experiments show that MRIG is able to outperform previous works dealing with the homogeneous version of the problem, which assumes the same loading capacity for all vehicles in the fleet. The numerical experiments also confirm that the proposed MRIG approach extends previous works by solving a more realistic HeVRPMD and provides the decision-maker with fleets with higher green levels.","PeriodicalId":49497,"journal":{"name":"Sort-Statistics and Operations Research Transactions","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90668759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Integer constraints for enhancing interpretability in linear regression 提高线性回归可解释性的整数约束

IF 1.6 4区数学

Sort-Statistics and Operations Research Transactions Pub Date : 2020-04-01 DOI: 10.2436/20.8080.02.95

E. Priego, Alba V. Olivares-Nadal, Pepa Ramírez Cobo

{"title":"Integer constraints for enhancing interpretability in linear regression","authors":"E. Priego, Alba V. Olivares-Nadal, Pepa Ramírez Cobo","doi":"10.2436/20.8080.02.95","DOIUrl":"https://doi.org/10.2436/20.8080.02.95","url":null,"abstract":"One of the main challenges researchers face is to identify the most relevant features in a prediction model. As a consequence, many regularized methods seeking sparsity have flourished. Although sparse, their solutions may not be interpretable in the presence of spurious coefficients and correlated features. In this paper we aim to enhance interpretability in linear regression in presence of multicollinearity by: (i) forcing the sign of the estimated coefficients to be consistent with the sign of the correlations between predictors, and (ii) avoiding spurious coefficients so that only significant features are represented in the model. This will be addressed by modelling constraints and adding them to an optimization problem expressing some estimation procedure such as ordinary least squares or the lasso. The so-obtained constrained regression models will become Mixed Integer Quadratic Problems. The numerical experiments carried out on real and simulated datasets show that tightening the search space of some standard linear regression models by adding the constraints modelling (i) and/or (ii) help to improve the sparsity and interpretability of the solutions with competitive predictive quality.","PeriodicalId":49497,"journal":{"name":"Sort-Statistics and Operations Research Transactions","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81714078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

On interpretations of tests and effect sizes in regression models with a compositional predictor 用成分预测器解释回归模型中的检验和效应大小

IF 1.6 4区数学

Sort-Statistics and Operations Research Transactions Pub Date : 2020-01-01 DOI: 10.2436/20.8080.02.100

G. Gallart, V. Pawlowsky-Glahn

引用次数: 20

Bartlett and Bartlett-type corrections for censored data from a Weibull distribution 来自威布尔分布的删减数据的Bartlett和Bartlett型校正

IF 1.6 4区数学

Sort-Statistics and Operations Research Transactions Pub Date : 2020-01-01 DOI: 10.2436/20.8080.02.97

Tiago M. Magalhães, D. Gallardo

引用次数: 5

Modelling count data using the logratio-normal-multinomial distribution 使用对数-正态-多项分布建模计数数据

IF 1.6 4区数学

Sort-Statistics and Operations Research Transactions Pub Date : 2020-01-01 DOI: 10.2436/20.8080.02.96

M. Comas-Cufí, J. Martín-Fernández, G. Mateu-Figueras, J. Palarea‐Albaladejo

引用次数: 2

Bayesian structured antedependence model proposals for longitudinal data 纵向数据的贝叶斯结构前相关模型建议

IF 1.6 4区数学

Sort-Statistics and Operations Research Transactions Pub Date : 2020-01-01 DOI: 10.2436/20.8080.02.99

Edwin Castillo-Carreno, Edilberto Cepeda-Cuervo, V. Núñez-Antón

{"title":"Bayesian structured antedependence model proposals for longitudinal data","authors":"Edwin Castillo-Carreno, Edilberto Cepeda-Cuervo, V. Núñez-Antón","doi":"10.2436/20.8080.02.99","DOIUrl":"https://doi.org/10.2436/20.8080.02.99","url":null,"abstract":"An important problem in Statistics is the study of longitudinal data taking into account the effect of other explanatory variables, such as treatments and time and, simultaneously, the incorporation into the model of the time dependence between observations on the same individual. The latter is specially relevant in the case of nonstationary correlations, and nonconstant variances for the different time point at which measurements are taken. Antedependence models constitute a well known commonly used set of models that can accommodate this behaviour. These covariance models can include too many parameters and estimation can be a complicated optimization problem requiring the use of complex algorithms and programming. In this paper, a new Bayesian approach to analyse longitudinal data within the context of antedependence models is proposed. This innovative approach takes into account the possibility of having nonstationary correlations and variances, and proposes a robust and computationally efficient estimation method for this type of data. We consider the joint modelling of the mean and covariance structures for the general antedependence model, estimating their parameters in a longitudinal data context. Our Bayesian approach is based on a generalization of the Gibbs sampling and Metropolis-Hastings by blocks algorithm, properly adapted to the antedependence models longitudinal data settings. Finally, we illustrate the proposed methodology by analysing several examples where antedependence models have been shown to be useful: the small mice, the speech recognition and the race data sets.","PeriodicalId":49497,"journal":{"name":"Sort-Statistics and Operations Research Transactions","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82916025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

False discovery rate control for grouped or discretely supported p-values with application to a neuroimaging study 在神经影像学研究中应用分组或离散支持p值的错误发现率控制

IF 1.6 4区数学

Sort-Statistics and Operations Research Transactions Pub Date : 2019-07-01 DOI: 10.2436/20.8080.02.87

H. Nguyen, Yohan Yee, G. McLachlan, J. Lerch

引用次数: 1

On the optimism correction of the area under the receiver operating characteristic curve in logistic prediction models logistic预测模型中接收者工作特征曲线下面积的乐观修正

IF 1.6 4区数学

Sort-Statistics and Operations Research Transactions Pub Date : 2019-06-11 DOI: 10.2436/20.8080.02.82

Amaia Iparragirre, Irantzu Barrio, M. Rodríguez-Álvarez

引用次数: 2

A simheuristic for routing electric vehicles with limited driving ranges and stochastic travel times 有限续驶里程和随机行驶时间下电动汽车路径的相似启发式算法

IF 1.6 4区数学

Sort-Statistics and Operations Research Transactions Pub Date : 2019-06-11 DOI: 10.2436/20.8080.02.77

Lorena Silvana Reyes Rubiano, D. Ferone, Ángel Alejandro Juan Pérez, Francisco Javier Faulín Fajardo

引用次数: 36

Internalizing negative externalities in vehicle routing problems through green taxes and green tolls 通过绿色税收和绿色通行费内部化车辆路线问题的负外部性

IF 1.6 4区数学

Sort-Statistics and Operations Research Transactions Pub Date : 2019-01-01 DOI: 10.2436/20.8080.02.80

Adrian Hernandez, Francisco Javier Faulín Fajardo

引用次数: 5