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Identifying Dynamic Shifts to Careless and Insufficient Effort Behavior in Questionnaire Responses; a Novel Approach and Experimental Validation Struct. Equ. Model. (IF 6.0) Pub Date : 2024-03-14 Zachary J. Roman, Patrick Schmidt, Jason M. Miller, Holger Brandt
Careless and insufficient effort responding (C/IER) is a situation where participants respond to survey instruments without considering the item content. This phenomena adds noise to data leading t...
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Covariance Matrix Estimation for High-Throughput Biomedical Data with Interconnected Communities Am. Stat. (IF 1.8) Pub Date : 2024-03-11 Yifan Yang, Chixiang Chen, Shuo Chen
Estimating a covariance matrix is central to high-dimensional data analysis. Empirical analyses of high-dimensional biomedical data, including genomics, proteomics, microbiome, and neuroimaging, am...
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Bayesian Structural Equation Models of Correlation Matrices Struct. Equ. Model. (IF 6.0) Pub Date : 2024-03-12 James Ohisei Uanhoro
We present a method for Bayesian structural equation modeling of sample correlation matrices as correlation structures. The method transforms the sample correlation matrix to an unbounded vector us...
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Direct Discrepancy Dynamic Fit Index Cutoffs for Arbitrary Covariance Structure Models Struct. Equ. Model. (IF 6.0) Pub Date : 2024-03-12 Daniel McNeish, Melissa G. Wolf
Despite the popularity of traditional fit index cutoffs like RMSEA ≤ .06 and CFI ≥ .95, several studies have noted issues with overgeneralizing traditional cutoffs. Computational methods have been ...
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Worst-case risk measures of stop-loss and limited loss random variables under distribution uncertainty with applications to robust reinsurance Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-12 Jun Cai, Fangda Liu, Mingren Yin
Stop-loss and limited loss random variables are two important transforms of a loss random variable and appear in many modelling problems in insurance, finance, and other fields. Risk levels of a loss variable and its transforms are often measured by risk measures. When only partial information on a loss variable is available, risk measures of the loss variable and its transforms cannot be evaluated
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Energy-saving time allocation strategy with uncertain dwell times in urban rail transit: Two-stage stochastic model and nested dynamic programming framework Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-12 Deheng Lian, Pengli Mo, Andrea D’Ariano, Ziyou Gao, Lixing Yang
During practical operations, the urban rail transit system always suffers from various uncertainties, especially the uncertain dwell times, which have a significant impact on the execution of the timetable and affects its performance, such as train energy consumption and timetable stability. Using multi-scenario dwell times to capture its uncertainty, a two-stage chance-constrained stochastic model
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Iterated local search with ejection chains for the space-free multi-row facility layout problem Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-12 Song Wu, Wei Yang, Saïd Hanafi, Christophe Wilbaut, Yang Wang
This paper presents an iterated local search algorithm based on ejection chains to solve the space-free multi-row facility layout problem. The aim of this problem is to find a non-overlapping layout of facilities on a given number of rows such that there is no space between two adjacent facilities. In addition, the left-most facility of the arrangement must have zero abscissa. Our algorithm looks for
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Clinical site selection problems with probabilistic constraints Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-11 Anh Ninh, Yunhong Bao, Daniel McGibney, Tuan Nguyen
Recruiting candidates globally and across multiple sites in different geographic regions is necessary to speed up the enrollment of clinical trials. While patient enrollment can benefit from this globalization, initiating clinical trials has become much more complicated. In the start-up stage, the sites must be selected out of a set of potential candidates around the globe based on the specifics of
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A branch-and-price algorithm for unrelated parallel machine scheduling with machine usage costs Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-11 Jianfu Chen, Chengbin Chu, Abderrahim Sahli, Kai Li
This paper considers unrelated parallel machine scheduling involving machine usage costs, in addition to classic job completion time-related costs. The usage cost of each machine is made up of a fixed usage cost and a variable usage cost proportional to the total processing time of the jobs assigned to it. These features model many practical situations where machine usage costs include, for example
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Towards the development of an explainable e-commerce fake review index: An attribute analytics approach Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-11 Ronnie Das, Wasim Ahmed, Kshitij Sharma, Mariann Hardey, Yogesh K. Dwivedi, Ziqi Zhang, Chrysostomos Apostolidis, Raffaele Filieri
Instruments of corporate risk and reputation assessment tools are quintessentially developed on structured quantitative data linked to financial ratios and macroeconomics. An emerging stream of studies has challenged this norm by demonstrating improved risk assessment and model prediction capabilities through unstructured textual corporate data. Fake online consumer reviews pose serious threats to
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Instance generation tool for on-demand transportation problems Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-11 Michell Queiroz, Flavien Lucas, Kenneth Sörensen
We present REQreate, a tool to generate instances for on-demand transportation problems. Such problems consist of optimizing vehicle routes according to passengers’ demand for transportation under space and time restrictions (called requests). REQreate is flexible and can be configured to generate instances for a variety of problems types in this problem class. In this paper, we exemplify this with
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Game of banks - biform game theoretical framework for automated teller machine network cost sharing Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-11 Tri-Dung Nguyen
Automated teller machines (ATM) play a major role in the world economy as they enable financial transactions and hence good exchanges and consumption. ATM transaction fees are incurred to cover the cost of running the network and these are often settled among the members including banks and cash machine operators. In this paper, we develop a novel biform game theoretic model for members to optimally
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A digital economy development index based on an improved hierarchical data envelopment analysis approach Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-08 Chuanyin Guo, Qiwei Song, Ming-Miin Yu, Jian Zhang
The digital economy is playing an increasingly important role in the global economy. National and international organizations commonly utilize a composite index composed of multi-dimensional indicators to monitor performance, analyse policies, and communicate in the digital economy. This study introduces a hierarchical framework for constructing a Digital Economy Development Index (DEDI). One of the
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Tree-Guided Rare Feature Selection and Logic Aggregation with Electronic Health Records Data J. Am. Stat. Assoc. (IF 3.7) Pub Date : 2024-03-07 Jianmin Chen, Robert H. Aseltine, Fei Wang, Kun Chen
Statistical learning with a large number of rare binary features is commonly encountered in analyzing electronic health records (EHR) data, especially in the modeling of disease onset with prior me...
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Martingale Methods in Statistics J. Am. Stat. Assoc. (IF 3.7) Pub Date : 2024-03-05 Insuk Seo
Published in Journal of the American Statistical Association (Vol. 119, No. 545, 2024)
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A novel model for transfer synchronization in transit networks and a Lagrangian-based heuristic solution method Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-06 Zahra Ansarilari, Merve Bodur, Amer Shalaby
To realize the benefits of network connectivity in transfer-based transit networks, it is critical to minimize transfer disutility for passengers by synchronizing timetables of intersecting routes. We propose a mixed-integer linear programming timetable synchronization model that incorporates new features, such as dwell time determination and vehicle capacity consideration, which have been largely
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Bike rebalancing: How to find a balanced matching in the k center problem? Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-06 Jinxiang Gan, Guochuan Zhang, Yuhao Zhang
In the bike-sharing system, inspired by the problem proposed by O’Mahony and Shmoys (AAAI 2015), we present a new model called the balanced center problem with matching constraints. Given a network containing the same number of two types of points, supply points and demand points, we aim to allocate (supply) centers for supply points, and (demand) centers for demand points. The supply centers should
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The Journal of the American Statistical Association 2023 Associate Editors J. Am. Stat. Assoc. (IF 3.7) Pub Date : 2024-03-05
Published in Journal of the American Statistical Association (Vol. 119, No. 545, 2024)
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Hub location with congestion and time-sensitive demand Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-05 Carmen-Ana Domínguez-Bravo, Elena Fernández, Armin Lüer-Villagra
This work studies the effect of hub congestion and time-sensitive demand on a hub-and-spoke location/allocation system. The Hub Location with Congestion and Time-sensitive Demand Problem is introduced, which combines these two main characteristics. On the one hand, hubs can be activated at several service levels, each of them characterized by a maximum capacity, expressed as the amount of flow that
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Stochastic modeling of integrated order fulfillment processes with delivery time promise: Order picking, batching, and last-mile delivery Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-04 G. Raj, D. Roy, R. de Koster, V. Bansal
To guarantee high customer service and short and accurate lead times, many e-commerce retailers have started to home deliver their customer orders within a few hours or even minutes, also known as quick-commerce order fulfillment. Quick-commerce order fulfillment consists of three main processes: order picking in the warehouse, order batching for delivery, and last-mile delivery. The ultimate delivery
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A genetic algorithm for the Resource-Constrained Project Scheduling Problem with Alternative Subgraphs using a boolean satisfiability solver Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-04 Tom Servranckx, José Coelho, Mario Vanhoucke
This study evaluates a new solution approach for the Resource-Constrained Project Scheduling with Alternative Subgraphs (RCPSP-AS) in case that complex relations (i.e. nested and linked alternatives) are considered. In the RCPSP-AS, the project activity structure is extended with alternative activity sequences. This implies that only a subset of all activities should be scheduled, which corresponds
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The wildfire suppression problem with multiple types of resources Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-04 Mualla Gonca Avci, Mustafa Avci, Maria Battarra, Güneş Erdoğan
The frequency and impact of wildfires have considerably increased in the past decade, due to the extreme weather conditions as well as the increased population density. The aim of this study is to introduce, model, and solve a wildfire suppression problem that involves multiple types of fire suppression resources and their operational characteristics. Two integer programming (IP) formulations, a basic
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Optimal decomposition approach for solving large nesting and scheduling problems of additive manufacturing systems Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-03 Paulo Jorge Nascimento, Cristóvão Silva, Carlos Henggeler Antunes, Samuel Moniz
This paper addresses the challenges associated with nesting and production scheduling in additive manufacturing (AM). The problem studied consists of grouping a set of parts into batches, which are then assigned to and sequenced across the available machines, guaranteeing the production of all parts. This work stands out by proposing exact methods for the AM nesting and scheduling problem considering
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Plant capacity utilization with piecewise Cobb-Douglas technology: Definition and interpretation Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-03 Xiangyang Tao, Qingxian An, Mark Goh
Convex and nonconvex nonparametric technologies have been applied to estimate plant capacity utilization. However, they face challenges in capturing the production characteristic that involves the simultaneous consideration of increasing, constant, and decreasing marginal production rates along the production surfaces, which may be inconsistent with the standard microeconomic production theory. This
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Locating charging stations and routing drones for efficient automated stocktaking Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-02 Panupong Vichitkunakorn, Simon Emde, Makusee Masae, Christoph H. Glock, Eric H. Grosse
Drones have received growing attention in logistics recently. One possible application is deploying drones for auditing inventory in warehouses. With the use of drones, warehouses are able to increase inventory record accuracy and decrease labor costs. In this research, we introduce the stocktaking drone routing problem (STDRP), which consists of routing a fleet of drones through a warehouse for stocktaking
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A sample robust optimal bidding model for a virtual power plant Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-02 Seokwoo Kim, Dong Gu Choi
In many energy markets, the trade amount of electricity must be committed to before the actual supply. This study explores one consecutive operational challenge for a virtual power plant—the optimal bidding for highly uncertain distributed energy resources in a day-ahead electricity market. The optimal bidding problem is formulated as a scenario-based multi-stage stochastic optimization model. However
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A unifying framework for selective routing problems Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-01 Cagla F. Dursunoglu, Okan Arslan, Sebnem Manolya Demir, Bahar Y. Kara, Gilbert Laporte
We present a unifying framework for Selective Routing Problems (SRPs) through a systematic analysis. The common goal in SRPs is to determine an optimal vehicle route to serve a subset of vertices while covering another subset. They arise in diverse fields such as logistics, public health, disaster response, and urban development. To establish a unifying framework for different but related problems
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Analysis of the impact of corrective actions for stochastic project networks Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-01 Forough Vaseghi, Annelies Martens, Mario Vanhoucke
In project management, a project plan is constructed that assigns a planned start time to each project activity. Based on this plan, the total planned project duration and cost can be determined. However, during project execution, deviations from the plan are inevitable due to uncertainty and variability. When these deviations endanger the timely completion of projects, the project manager should take
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Recourse strategy for the routing problem of mobile parcel lockers with time windows under uncertain demands Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-01 Yang Wang, Mengyu Bi, Jianhui Lai, Chenxi Wang, Yanyan Chen, José Holguín-Veras
It is expected that mobile parcel lockers (MPLs) will provide more responsive and flexible service to the increasing variation of demand than fixed parcel lockers. However, the service provided by MPLs following planned routes can be degraded and even fail due to the demand uncertainty, such as demand volume and pickup time. In this study, we propose an optimization approach integrated with the recourse
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Order consolidation in warehouses: The loop sorter scheduling problem Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-01 Nils Boysen, Konrad Stephan, Stefan Schwerdfeger
To meet today’s ambitious order throughput targets, many distribution centers, especially those operated by online retailers, apply batching and zoning in their picker-to-parts warehouses. These order retrieval policies improve the pick density per tour by unifying multiple customer orders to larger pick lists and allow a parallelization of the picking process among multiple zones, respectively. The
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How to optimize container withholding decisions for reuse in the hinterland? Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-01 Benjamin Legros, Jan Fransoo, Oualid Jouini
This study investigates how a hinterland consignee (importer) makes decisions regarding the storage of empty containers for reuse by a shipper (exporter). The system is modeled as a double-ended queue with non-zero matching times, limited truck resources, and both consignee and shipper having fixed withholding capacities. The consignee’s withholding threshold is strategically set to minimize overall
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Exploiting symmetry for the job sequencing and tool switching problem Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-01 Najmaddin Akhundov, James Ostrowski
The Job Sequencing and Tool Switching Problem (SSP), a well-known combinatorial optimization problem in the domain of Flexible Manufacturing Systems (FMS), is studied in this article. The aim of this research is to improve the currently known exact solution methodology for this -hard problem. We propose a new integer linear programming approach with symmetry-breaking and tightening cuts that provably
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The Hamiltonian p-median problem: Polyhedral results and branch-and-cut algorithms Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-01 Michele Barbato, Luís Gouveia
In this paper we study the Hamiltonian -median problem, in which we are given an edge-weighted graph and we are asked to determine vertex-disjoint cycles spanning all vertices of the graph and having minimum total weight. We introduce two new families of valid inequalities for a formulation of the problem in the space of edge variables. Each one of the families forbids solutions to the 2-factor relaxation
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Mixed-integer linear programming formulations and column generation algorithms for the Minimum Normalized Cuts problem on networks Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-01 Diego Ponce, Justo Puerto, Francisco Temprano
This paper deals with the -way normalized cut problem in complex networks. It presents a methodology that uses mathematical optimization to provide mixed-integer linear programming formulations for the problem. The paper also develops a branch-and-price algorithm for the above-mentioned problem which scales better than the compact formulations. Additionally, a heuristic algorithm which is able to approximate
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Scheduling with cardinality dependent unavailability periods Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-01 G. Jaykrishnan, Asaf Levin
We consider non-preemptive scheduling problems on parallel identical machines where machines change their status from being available to being unavailable and vice versa along the time horizon. The particular form of unavailability we consider is when the starting time of each downtime depends upon the cardinality of the job subset processed on that machine since the previous downtime. We consider
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Fueling the future: Overcoming the barriers to market development of renewable fuels in Germany using a novel analytical approach Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-03-01 Ali Ebadi Torkayesh, Sepehr Hendiani, Grit Walther, Sandra Venghaus
Germany has set ambitious targets for reducing greenhouse gas (GHG) emissions, namely by 65% until 2030 (compared to the 1990 level) and achieving climate neutrality by 2045. Although GHG emissions have decreased in most sectors, the transport sector has experienced failed reduction attempts. Renewable fuels are promising sustainable fuel alternatives that can replace current market-dominant fossil
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Higher-order assortativity for directed weighted networks and Markov chains Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-02-29 Alberto Arcagni, Roy Cerqueti, Rosanna Grassi
In this paper, we propose a new class of assortativity measures for weighted and directed networks. We extend Newman’s classical degree–degree assortativity by considering node attributes other than degree, and we propose connections among nodes via directed walks of length greater than one, thus obtaining higher-order assortativity. We test the new measure in the paradigmatic case of the world trade
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Integrated inventory replenishment and online demand allocation decisions for an omnichannel retailer with ship-from-store strategy Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-02-28 Vishal Bansal, Arnab Bisi, Debjit Roy, Prahalad Venkateshan
Retailing has changed dramatically from single-channel brick-and-mortar stores to multi-channel and omnichannel retailers over the last few decades. Omnichannel retailers employ different strategies to integrate online and offline sales channels as well as order fulfillment processes. Among these strategies, the ship-from-store is the most popular and widely accepted among retailers. It enables retailers
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Optimizing location-routing and demand allocation in the household waste collection system using a branch-and-price algorithm Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-02-27 Jialin Han, Jiaxiang Zhang, Haoyue Guo, Ning Zhang
In catering to the rapid development of urbanization and the growing urban population, it is essential to design an efficient and effective household waste collection system for guaranteeing a favorable ecological environment in cities. This paper focuses on a location-routing and demand allocation problem (LRDAP) in the household waste collection system where the household waste is initially allocated
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Logistics sourcing of e-commerce firms considering promised delivery time and environmental sustainability Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-02-27 Canran Gong, Huaming Song, Daqiang Chen, Steven James Day, Joshua Ignatius
Online consumers prioritise swift and dependable deliveries but are also concerned about the environmental repercussions of e-commerce, such as carbon emissions and packaging waste. E-commerce firms, therefore, grapple with balancing short promised delivery times (PDT) and environmental sustainability in a competitive landscape. Through a game-theoretic lens, this study delves into the logistics choices
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A Technique for Efficient Estimation of Dynamic Structural Equation Models: A Case Study Struct. Equ. Model. (IF 6.0) Pub Date : 2024-02-22 Leonidas Sakalauskas, Vytautas Dulskis, Darius Plikynas
Dynamic structural equation models (DSEM) are designed for time series analysis of latent structures. Inherent to the application of DSEM is model parameter estimation, which has to be addressed in...
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Improving order picking efficiency through storage assignment optimization in robotic mobile fulfillment systems Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-02-24 Yanling Zhuang, Yun Zhou, Elkafi Hassini, Yufei Yuan, Xiangpei Hu
The order picking efficiency in robotic mobile fulfillment systems is not only determined by the order and rack processing sequences, but also by the product distribution on the racks. In this paper, we focus on long-term planning based on historical order data to identify the optimal distribution of SKUs on racks for order picking operation improvement. This product distribution problem is formulated
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New exact and heuristic algorithms for general production and delivery integration Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-02-24 Xianyan Yang, Feng Li, Zhixue Liu, Zhou Xu
This study considers a general production and delivery integration problem, commonly faced by a manufacturer that adopts make-to-order and commit-to-delivery business strategies. In the problem, the manufacturer determines acceptance or rejection of customers, produces products for accepted customers, and cooperates with third-party logistics providers who offer multiple shipping modes chosen by the
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Robust Personalized Federated Learning with Sparse Penalization* J. Am. Stat. Assoc. (IF 3.7) Pub Date : 2024-02-23 Weidong Liu, Xiaojun Mao, Xiaofei Zhang, Xin Zhang
Federated learning (FL) is an emerging topic due to its advantage in collaborative learning with distributed data. Due to the heterogeneity in the local data-generating mechanism, it is important t...
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Doubly Flexible Estimation under Label Shift J. Am. Stat. Assoc. (IF 3.7) Pub Date : 2024-02-21 Seong-ho Lee, Yanyuan Ma, Jiwei Zhao
In studies ranging from clinical medicine to policy research, complete data are usually available from a population P , but the quantity of interest is often sought for a related but different popu...
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A branch-and-bound algorithm with growing datasets for large-scale parameter estimation Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-02-23 Susanne Sass, Alexander Mitsos, Dominik Bongartz, Ian H. Bell, Nikolay I. Nikolov, Angelos Tsoukalas
The solution of nonconvex parameter estimation problems with deterministic global optimization methods is desirable but challenging, especially if large measurement datasets are considered. We propose to exploit the structure of this class of optimization problems to enable their solution with the spatial branch-and-bound algorithm. In detail, we start with a reduced dataset in the root node and progressively
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Fitting Cross-Lagged Panel Models with the Residual Structural Equations Approach Struct. Equ. Model. (IF 6.0) Pub Date : 2024-02-22 Ming-Chi Tseng
This study simplifies the seven different cross-lagged panel models (CLPMs) by using the RSEM model for both inter-individual and intra-individual structures. In addition, the study incorporates th...
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Dynamic Structural Equation Models with Missing Data: Data Requirements on N and T Struct. Equ. Model. (IF 6.0) Pub Date : 2024-02-22 Yuan Fang, Lijuan Wang
Dynamic structural equation modeling (DSEM) is a useful technique for analyzing intensive longitudinal data. A challenge of applying DSEM is the missing data problem. The impact of missing data on ...
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The maximum length car sequencing problem Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-02-22 Lara Pontes, Carlos Neves, Anand Subramanian, Maria Battarra
This paper introduces the maximum length car sequencing problem to support the assembly operations of a multinational automotive company. We propose an integer linear programming (ILP) formulation to schedule the maximum number of cars without violating the so-called option constraints. In addition, we present valid combinatorial lower and upper bounds, which can be calculated in less than 0.01 s,
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A distributionally robust chance-constrained kernel-free quadratic surface support vector machine Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-02-22 Fengming Lin, Shu-Cherng Fang, Xiaolei Fang, Zheming Gao, Jian Luo
This paper studies the problem of constructing a robust nonlinear classifier when the data set involves uncertainty and only the first- and second-order moments are known a priori. A distributionally robust chance-constrained kernel-free quadratic surface support vector machine (SVM) model is proposed using the moment information of the uncertain data. The proposed model is reformulated as a semidefinite
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On the term “randomization test” Am. Stat. (IF 1.8) Pub Date : 2024-02-21 Jesse Hemerik
There is no consensus on the meaning of the term “randomization test”. Contradictory uses of the term are leading to confusion, misunderstandings and indeed invalid data analyses. A main source of ...
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Bias-Adjusted Three-Step Multilevel Latent Class Modeling with Covariates Struct. Equ. Model. (IF 6.0) Pub Date : 2024-02-16 Johan Lyrvall, Zsuzsa Bakk, Jennifer Oser, Roberto Di Mari
We present a bias-adjusted three-step estimation approach for multilevel latent class models (LC) with covariates. The proposed approach involves (1) fitting a single-level measurement model while ...
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D-Scoring Method of Measurement Classical and Latent Frameworks Struct. Equ. Model. (IF 6.0) Pub Date : 2024-02-16 Ademola B. Ajayi
Published in Structural Equation Modeling: A Multidisciplinary Journal (Ahead of Print, 2024)
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Tackling Challenges in Data Pooling: Missing Data Handling in Latent Variable Models with Continuous and Categorical Indicators Struct. Equ. Model. (IF 6.0) Pub Date : 2024-02-16 Lihan Chen, Milica Miočević, Carl F. Falk
Data pooling is a powerful strategy in empirical research. However, combining multiple datasets often results in a large amount of missing data, as variables that are not present in some datasets e...
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Measurement Invariance is Not Sufficient for Meaningful and Valid Group Comparisons: A Note on Robitzsch and Lüdtke Struct. Equ. Model. (IF 6.0) Pub Date : 2024-02-16 Tenko Raykov
This note demonstrates that measurement invariance does not guarantee meaningful and valid group comparisons in multiple-population settings. The article follows on a recent critical discussion by ...
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Agency Models in Online Platforms: A Review of Recent Developments and Future Prospects Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-02-17 Yinliang (Ricky) Tan, Chuanbin Yu, Yang Liu, Quan Zheng
Over the past decade, the ascendancy of the platform economy has led to a significant shift by numerous online merchants, transitioning from the conventional wholesale model to the agency model. Within the agency model, suppliers control pricing decisions, and in exchange for leveraging the online marketplace to access consumers, they apportion a segment of the revenue to the retailers. Reports indicate
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New Exact Algorithm for the integrated train timetabling and rolling stock circulation planning problem with stochastic demand Eur. J. Oper. Res. (IF 6.4) Pub Date : 2024-02-16 Hanchuan Pan, Lixing Yang, Zhe Liang, Hai Yang
This paper studies an integrated train timetabling and rolling stock circulation planning problem with stochastic demand and flexible train composition (TRSF). A novel stochastic integer programming model, which is formulated on a space-time underlying network to simultaneously optimize the train timetable and rolling stock circulation plan with flexible train composition, is proposed by explicitly
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Modeling Recurrent Failures on Large Directed Networks J. Am. Stat. Assoc. (IF 3.7) Pub Date : 2024-02-15 Qingqing Zhai, Zhisheng Ye, Cheng Li, Matthew Revie, David B. Dunson
Many lifeline infrastructure systems consist of thousands of components configured in a complex directed network. Disruption of the infrastructure constitutes a recurrent failure process over a dir...
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Addressing Multiple Detection Limits with Semiparametric Cumulative Probability Models J. Am. Stat. Assoc. (IF 3.7) Pub Date : 2024-02-13 Yuqi Tian, Chun Li, Shengxin Tu, Nathan T. James, Frank E. Harrell, Bryan E. Shepherd
Detection limits (DLs), where a variable cannot be measured outside of a certain range, are common in research. DLs may vary across study sites or over time. Most approaches to handling DLs in resp...