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Coordination of master planning in supply chains Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-02-05 Martin Albrecht
This paper proposes a new mechanism for coordinating master planning in a buyer–supplier supply chain. Parties take different roles in the mechanism: there is an informed party (IP) and a reporting party (RP). The mechanism consists of three steps. First, the RP defines a lump sum payment, which he will receive if a supply proposal that deviates from the default is implemented. Second, parties generate
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Single-machine scheduling with fixed energy recharging times to minimize the number of late jobs and the number of just-in-time jobs: A parameterized complexity analysis Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-02-03 Renjie Yu, Daniel Oron
We study single-machine scheduling problems where processing each job requires both processing time and rechargeable energy. Subject to a predefined energy capacity, energy can be recharged after each job during a fixed recharging period. Our focus is on two due date-related scheduling criteria: minimizing the number of late jobs and maximizing the weighted number of jobs completed exactly at their
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Deep Controlled Learning for Inventory Control Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-31 Tarkan Temiz?z, Christina Imdahl, Remco Dijkman, Douniel Lamghari-Idrissi, Willem van Jaarsveld
The application of Deep Reinforcement Learning (DRL) to inventory management is an emerging field. However, traditional DRL algorithms, originally developed for diverse domains such as game-playing and robotics, may not be well-suited for the specific challenges posed by inventory management. Consequently, these algorithms often fail to outperform established heuristics; for instance, no existing DRL
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A branch-and-price algorithm for fast and equitable last-mile relief aid distribution Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-30 Mahdi Mostajabdaveh, F. Sibel Salman, Walter J. Gutjahr
The distribution of relief supplies to shelters is a critical aspect of post-disaster humanitarian logistics. In major disasters, prepositioned supplies often fall short of meeting all demands. We address the problem of planning vehicle routes from a distribution center to shelters while allocating limited relief supplies. To balance efficiency and equity, we formulate a bi-objective problem: minimizing
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Sequential product launches with post-sale updates Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-30 Monire Jalili, Michael S. Pangburn, Euthemia Stavrulaki, Shubin Xu
As technology evolves, a seller may offer sequential releases of its product over time, with new versions offering superior performance. Beyond offering new product releases over time, sellers now increasingly have the option of offering post-sale software updates, thereby potentially extending product longevity. The potential to change product life cycles via software updates is of strategic importance
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Monitoring bank risk around the world using unsupervised learning Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-28 Mathieu Mercadier, Amine Tarazi, Paul Armand, Jean-Pierre Lardy
This paper provides a transparent and dynamic decision support tool that ranks clusters of listed banks worldwide by riskiness. It is designed to be flexible in updating and editing the values and quantities of banks, indicators, and clusters. For constructing this tool, a large set of stand-alone and systemic risk indicators are computed and reduced to fewer representative factors. These factors are
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Stochastic model for physician staffing and scheduling in emergency departments with multiple treatment stages Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-26 Janaina F. Marchesi, Silvio Hamacher, Igor Tona Peres
We propose a new solution for the Emergency Department (ED) staffing and scheduling problem, considering uncertainty in patient arrival patterns, multiple treatment stages, and resource capacity. A two-stage stochastic mathematical programming model was developed. We employed a Sample Average Approximation (SAA) method to generate scenarios and a discrete event simulation to evaluate the results. The
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A new effective heuristic for the Prisoner Transportation Problem Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-25 Luciano Ferreira, Marcos Vinicius Milan Maciel, José Valério de Carvalho, Elsa Silva, Filipe Pereira Alvelos
The Prisoner Transportation Problem is an NP-hard combinatorial problem and a complex variant of the Dial-a-Ride Problem. Given a set of requests for pick-up and delivery and a homogeneous fleet, it consists of assigning requests to vehicles to serve all requests, respecting the problem constraints such as route duration, capacity, ride time, time windows, multi-compartment assignment of conflicting
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Trade-off between utility and fairness in two-agent single-machine scheduling Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-25 Alessandro Agnetis, Mario Benini, Gaia Nicosia, Andrea Pacifici
We consider the problem arising when two agents, each owning a set of jobs, compete to schedule their jobs on a common processing resource. Each schedule implies a certain utility for each agent and an overall system utility. We are interested in solutions that incorporate some criterion of fairness for the agents and, at the same time, are satisfactory from the viewpoint of system utility. More precisely
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From collaborative filtering to deep learning: Advancing recommender systems with longitudinal data in the financial services industry Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-25 Stephanie Beyer Díaz, Kristof Coussement, Arno De Caigny
Recommender systems (RS) are highly relevant for multiple domains, allowing to construct personalized suggestions for consumers. Previous studies have strongly focused on collaborative filtering approaches, but the inclusion of longitudinal data (LD) has received limited attention. To address this gap, we investigate the impact of incorporating LD for recommendations, comparing traditional collaborative
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Optimal outbound shipment policy for an inventory system with advance demand information Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-24 Jana Ralfs, Dai T. Pham, Gudrun P. Kiesmüller
This paper examines a single-echelon inventory system that fulfills stochastic orders from a production facility using a time-based shipment consolidation strategy. In this system, the production facility provides advance demand information to the warehouse, ensuring that all orders are placed with a positive demand lead time. Using value iteration, we identify the optimal outbound shipment quantities
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The first mile is the hardest: A deep learning-assisted matheuristic for container assignment in first-mile logistics Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-24 Simon Emde, Ana Alina Tudoran
Urban logistics has been recognized as one of the most complex and expensive part of e-commerce supply chains. An increasing share of this complexity comes from the first mile, where shipments are initially picked up to be fed into the transportation network. First-mile pickup volumes have become fragmented due to the enormous growth of e-commerce marketplaces, which allow even small-size vendors access
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Dynamic worker allocation in Seru production systems with actor–critic and pointer networks Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-24 Dongni Li, Hongbo Jin, Yaoxin Zhang
Following the rapid evolution of manufacturing industries, customer demands may change dramatically, which challenges the conventional production systems. Seru production system (SPS) is a key to deal with uncertain varieties and fluctuating volumes. In dynamic scenarios, orders with uncertain demands arrive over time. For each arriving order, appropriate workers should be allocated to assemble it
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Integrating public transport in sustainable last-mile delivery: Column generation approaches Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-24 Diego Delle Donne, Alberto Santini, Claudia Archetti
We tackle the problem of coordinating a three-echelon last-mile delivery system. In the first echelon, trucks transport parcels from distribution centres outside the city to public transport stops. In the second echelon, the parcels move on public transport and reach the city centre. In the third echelon, zero-emission vehicles pick up the parcels at public transport stops and deliver them to customers
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The interplay between charitable donation strategies and sales mode selection in the platform Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-23 Chen Zhu, Georges Zaccour
Motivated by the emergence of offline and online donations, this paper explores the interplay between charitable donations and strategic choice of sales mode in a philanthropic supply chain consisting of a manufacturer and a platform. We consider two donation strategies, offline donations and both offline and online donations that are traceable by blockchain technology, and two business models, i.e
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The Dynamic Team Orienteering Problem Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-22 Emre Kirac, Ashlea Bennett Milburn, Ridvan Gedik
This study introduces a new dynamic routing problem, namely the Dynamic Team Orienteering Problem (DTOP), which is a dynamic variant of the Team Orienteering Problem (TOP). In the DTOP, some customer locations are known a priori, while others are dynamic, with each location associated with a profit value. The goal is to maximize the sum of collected profits by visiting a set of customer locations within
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Formulations and Branch-and-cut algorithms for the Period Travelling Salesman Problem Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-22 Sofia Henriques, Ana Paias
In this work, we address two variants of the Period Travelling Salesman Problem: one where some nodes cannot be visited consecutively over the time horizon, and another one where this restriction is not imposed. A new flow-based formulation that uses specific information about the visit patterns of nodes is studied and empirical tests show that it is able to solve test instances where a flow-based
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The collaborative berth allocation problem with row-generation algorithms for stable cost allocations Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-22 Xiaohuan Lyu, Eduardo Lalla-Ruiz, Frederik Schulte
Recent supply chain disruptions and crisis response policies (e.g., the COVID-19 pandemic and the Red Sea crisis) have highlighted the role of container terminals as crucial and scarce resources in the global economy. To tackle these challenges, the industry increasingly aims for advanced operational collaboration among multiple stakeholders, as demonstrated by the ambitions of the recently founded
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Data-driven condition-based maintenance optimization given limited data Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-21 Yue Cai, Bram de Jonge, Ruud H. Teunter
Unexpected failures of operating systems can result in severe consequences and huge economic losses. To prevent them, preventive maintenance based on condition data can be performed. Existing studies either rely on the assumption of a known deterioration process or an abundance of data. However, in practice, it is unlikely that the deterioration process is known, and data is often limited (to a few
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Managing social responsibility efforts with the consideration of violation probability Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-21 Jiayan Xu, Housheng Duan, Sijing Deng
Corporate social responsibility (CSR) has a strong impact on the external image of the enterprise. The violation of CSR not only harms the enterprise but also negatively affects other firms in the supply chain. This paper establishes a game-theoretical model to study the management of social responsibility efforts with considerations of violation probability. The upstream manufacturer and downstream
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Sustainable optimal stock portfolios: What relationship between sustainability and performance? Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-19 Beatrice Bertelli, Costanza Torricelli
The aim of this paper is to compare different strategies to combine sustainability and optimality in stock portfolios to assess whether there is an association between their average ESG (Environmental, Social, Governance) score and their financial performance and, if so, whether it depends on the specific strategy used. To this end, we confront the risk-adjusted performance of three ESG-compliant optimal
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Dynamic pharmaceutical product portfolio management with flexible resource profiles Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-19 Xin Fei, Jürgen Branke, Nal?n Gülp?nar
The pharmaceutical industry faces growing pressure to develop innovative, affordable products faster. Completing clinical trials on time is crucial, as revenue strongly depends on the finite patent protection. In this paper, we consider dynamic resource allocation for pharmaceutical product portfolio management and clinical trial scheduling, proposing a modelling framework, where resource profiles
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Novel adaptive parameter fractional-order gradient descent learning for stock selection decision support systems Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-18 Mingjie Ma, Siyuan Chen, Lunan Zheng
Gradient descent methods are widely used as optimization algorithms for updating neural network weights. With advancements in fractional-order calculus, fractional-order gradient descent algorithms have demonstrated superior optimization performance. Nevertheless, existing fractional-order gradient descent algorithms have shortcomings in terms of structural design and theoretical derivation. Specifically
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Biform game consensus analysis of group decision making with unconnected social network Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-16 Jie Tang, Zi-Jun Li, Fan-Yong Meng, Zai-Wu Gong, Witold Pedrycz
In today's network era, people's decisions are susceptibly influenced by others, especially the ones they trust. This study confines to studying social network group decision making (SNGDM). Due to the mutual influence of consensus level and consensus adjustment among decision makers (DMs), this study utilizes biform game theory to propose an innovative consensus mechanism for facilitating group decision
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Strategic decentralization of self-branded and contract manufacturing businesses Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-16 Wei Li, Yanglei Li, Jing Chen, Bintong Chen
This paper explores the incentive of a competitive contract manufacturer (CCM) to adopt a decentralized structure by segregating contract manufacturing from its self-branded business. We consider an original equipment manufacturer (OEM) with the option to outsource production either to a CCM producing its self-branded product, or to a non-competitive contract manufacturer (NCM) also serving another
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On enhancing the explainability and fairness of tree ensembles Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-16 Emilio Carrizosa, Kseniia Kurishchenko, Dolores Romero Morales
Tree ensembles are one of the most powerful methodologies in Machine Learning. In this paper, we investigate how to make tree ensembles more flexible to incorporate explainability and fairness in the training process, possibly at the expense of a decrease in accuracy. While explainability helps the user understand the key features that play a role in the classification task, with fairness we ensure
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Structure identification for partially linear partially concave models Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-15 Jianhui Xie, Zhewen Pan
Partially linear partially concave models are semiparametric regression models that can capture linear and concavity-constrained nonlinear effects within one framework. A fundamental problem of this kind of model is deciding which covariates have linear effects and which covariates have strictly concave effects. Assuming that the true regression function is partially linear partially concave and sparse
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Flexibility-based price discrimination in a competitive context considering consumers’ socioeconomic status Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-15 Jian Zhang, Emily B. Laidlaw, Raymond A. Patterson
This study examines the impact of flexibility-based price discrimination (FBPD) on the pricing and quality strategy of the adopting firm and its competitor, as well as the impact on the welfare of consumers. We assume that the inflexible consumers being targeted for price discrimination can be either high-income consumers or low-income consumers, and the high-income consumers are more sensitive to
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Predictive distributions and the market return: The role of market illiquidity Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-13 Michael Ellington, Maria Kalli
This paper evaluates the role of volatility-free stock market illiquidity proxies in forecasting monthly stock market returns. We adopt a probabilistic approach to multivariate time-series modelling using Bayesian nonparametric vector autoregressions. These models flexibly capture complex joint dynamics among financial variables through data-driven regime switching. Out-of-sample forecasts maintain
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Formulating human risk response in epidemic models: Exogenous vs endogenous approaches Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-11 Leah LeJeune, Navid Ghaffarzadegan, Lauren M. Childs, Omar Saucedo
The recent pandemic emphasized the need to consider the role of human behavior in shaping epidemic dynamics. In particular, it is necessary to extend beyond the classical epidemiological structures to fully capture the interplay between the spread of disease and how people respond. Here, we focus on the challenge of incorporating change in human behavior in the form of “risk response” into compartmental
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Optimal resource allocation: Convex quantile regression approach Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-10 Sheng Dai, Natalia Kuosmanen, Timo Kuosmanen, Juuso Liesi?
Optimal allocation of resources across sub-units in the context of centralized decision-making systems such as bank branches or supermarket chains is a classical application of operations research and management science. In this paper, we develop quantile allocation models to examine how much the output and productivity could potentially increase if the resources were efficiently allocated between
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Fifty years at the interface between financial modeling and operations research Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-07 Frank J. Fabozzi, Maria Cristina Recchioni, Roberto Renò
Over the last fifty years, there has been an increasing intersection of methodologies, applications, and contributions at the frontier of finance and operations research. This invited paper selectively reviews this literature, aiming to provide a building block for future research at the intersection between the two fields. Our review revolves around four main themes: option pricing, interest rate
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Impact of loyal and new customer segments on product upgrades: The role of quality differentiation through online reviews Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-07 Qiang Huang, Joshua Ignatius, Huaming Song, Junsong Bian, Canran Gong
Firms often strive to expand their market share beyond their established customer base by launching quality upgrades in their products. They recognize that customers often gauge product quality through online reviews. We develop an analytical model to examine the quality upgrade strategies of two competing firms, revealing two potential market equilibria. In the unilateral upgrading equilibrium where
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Coordinate or collaborate? Reducing food waste in perishable-product supply chains Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-07 Navid Mohamadi, Sandra Transchel, Jan C. Fransoo
Reducing food waste in supply chains (SCs) with multiple decision-makers is challenging. A common approach grocery retailers use to reduce waste is requiring manufacturers to only send products with a long remaining shelf life (“minimum life on receipt”-MLOR). However, its impact on manufacturers remains unclear.
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Fairness in repetitive scheduling Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-06 Danny Hermelin, Hendrik Molter, Rolf Niedermeier, Michael Pinedo, Dvir Shabtay
Recent research found that fairness plays a key role in customer satisfaction. Therefore, many manufacturing and services industries have become aware of the need to treat customers fairly. Still, there is a huge lack of models that enable industries to make operational decisions fairly, such as a fair scheduling of the customers’ jobs. Our main aim in this research is to provide a unified framework
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Forecast accuracy and inventory performance: Insights on their relationship from the M5 competition data Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-06 Evangelos Theodorou, Evangelos Spiliotis, Vassilios Assimakopoulos
Although it is generally accepted that more accurate forecasts contribute towards better inventory performance, this relationship may often be weak, also depending on the structural characteristics of the products being forecast, the inventory policy considered, and the underlying expenses, among others. To empirically explore the connection between forecast accuracy and key costs associated with inventory
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Investigating the research and development performance of Chinese industry: A two-stage prospect data envelopment analysis approach Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-04 Hui-hui Liu, Guo-liang Yang, Jian-wei Gao, Ya-ping Wang, Guo-hua Ni
With growing investments inindustry research and development (R&D) innovation in China, evaluating whether R&D resources assigned to industries areeffectively used is essential. However, limited research has been conducted on the assessment of R&D effectiveness in Chinese industries that encompasses both the internal process of R&D production and the psychological risks encountered by decision-makers
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Exploring the discrete and continuous edge improvement problems: Models and algorithms Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-04 Esra Koca, A. Burak Pa?
In this paper, we investigate the edge improvement problem where the fixed edge traversal time assumption of the traditional network flow problems is relaxed. We consider two variants of the problem: one where improvement decisions are restricted to a discrete set (discrete edge improvement problem), and the other where they can take any value within a specified range (continuous edge improvement problem)
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Judgmental selection of parameters for simple forecasting models Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-04 Fotios Petropoulos, Evangelos Spiliotis
In an era dominated by big data and machine and deep learning solutions, judgment has still an important role to play in decision making. Behavioural operations are on the rise as judgment complements automated algorithms in many practical settings. Over the years, new and exciting uses of judgment have emerged, with some providing fresh and innovative insights on algorithmic approaches. The forecasting
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Risk-sharing in energy communities Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-04 Ibrahim Abada, Andreas Ehrenmann, Xavier Lambin
Energy communities are considered one of the pillars of the energy transition, owing to the rapid development of digital smart appliances and metering. They benefit from strong political support to accommodate their penetration in Europe. Nevertheless, the pace at which they have developed has been very slow compared with what was expected a decade ago. Many articles have revealed some of the underlying
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Queues with service resetting Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-03 Ofek Lauber Bonomo, Uri Yechiali, Shlomi Reuveni
Service time fluctuations heavily affect the performance of queueing systems, causing long waiting times and backlogs. Recently, it was shown that when service times are solely determined by the server, service resetting can mitigate the deleterious effects of service time fluctuations and drastically improve queue performance (Bonomo et al., 2022). Yet, in many queueing systems, service times have
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Do stable outcomes survive in marriage problems with myopic and farsighted players? Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-01 P. Jean-Jacques Herings, Ana Mauleon, Vincent Vannetelbosch
We consider marriage problems where myopic and farsighted players interact and analyze these problems by means of the myopic-farsighted stable set. We require that coalition members are only willing to deviate if they all strictly benefit from doing so. Our first main result establishes the equivalence of myopic-farsighted stable sets based on arbitrary coalitional deviations and those based on pairwise
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The Copeland ratio ranking method for abstract decision problems Eur. J. Oper. Res. (IF 6.0) Pub Date : 2025-01-01 Weibin Han, Adrian Van Deemen
This paper deals with the problem of ranking a finite number of alternatives on the basis of a dominance relation. We firstly investigate some disadvantages of the Copeland ranking method, of the degree ratio ranking method and of the modified degree ratio ranking method which were characterized by using clone properties and classical axiomatic properties. Then, we introduce some alternative axiomatic
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Exact algorithms for routing electric autonomous mobile robots in intralogistics Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-12-31 Anne Meyer, Timo Gschwind, Boris Amberg, Dominik Colling
In intralogistics and manufacturing, autonomous mobile robots (AMRs) are usually electrically powered and recharged by battery swapping or induction. We investigate AMR route planning in these settings by studying different variants of the electric vehicle routing problem with due dates (EVRPD). We consider three common recharging strategies: battery swapping, inductive recharging with full recharges
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Exact and heuristic algorithms for cardinality-constrained assortment optimization problem under the cross-nested logit model Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-12-31 Le Zhang, Shadi Sharif Azadeh, Hai Jiang
We study a class of assortment optimization problems where customers choose products according to the cross-nested logit (CNL) model and the number of products offered in the assortment cannot exceed a fixed number. Currently, no exact method exists for this NP-hard problem that can efficiently solve even small instances (e.g., 50 products with a cardinality limit of 10). In this paper, we propose
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Simulative assessment of patrol car allocation and response time Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-12-31 Tobias Cors, Malte Fliedner, Knut Haase, Tobias Vl?ek
Capacity planning of police resources is crucial to operating an effective and robust police service. However, due to the high operational heterogeneity and variability among different calls for service, key performance estimates that link resource allocation and utilization to emergency response times are a challenging task in and of itself. In the literature, two main instruments are proposed to
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Business cycle and realized losses in the consumer credit industry Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-12-30 Walter Distaso, Francesco Roccazzella, Frédéric Vrins
We investigate the determinants of losses given default (LGD) in consumer credit. Utilizing a unique dataset encompassing over 6 million observations of Italian consumer credit over a long time span, we find that macroeconomic and social (MS) variables significantly enhance the forecasting performance at both individual and portfolio levels, improving R2 by up to 10 percentage points. Our findings
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Measuring technical efficiency under variable returns to scale using Debreu's loss function Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-12-29 Juan José Díaz-Hernández, David-José Cova-Alonso, Eduardo Martínez-Budría
This paper proposes a model that makes two contributions to the measurement of technical efficiency under a technology with variable returns to scale. First, the criteria for identifying an optimal benchmark are not limited to technical dominance and Pareto efficiency, but also include maximum average productivity, defined as the ratio between a weighted linear aggregate of outputs and inputs.
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Fifty years of Data Envelopment Analysis Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-12-28 Anna Mergoni, Ali Emrouznejad, Kristof De Witte
Data Envelopment Analysis (DEA) has emerged as a powerful analytical tool, revolutionising the field of Operational Research (OR) and contributing to advancements in performance evaluation methodologies. This practical literature review delves into the extensive body of research surrounding DEA, focusing particularly on its evolution within the last 50 years. Drawing upon a comprehensive analysis of
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Approximating [formula omitted] queues with deep learning Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-12-28 Eliran Sherzer, Opher Baron, Dmitry Krass, Yehezkel Resheff
Many real-world queueing systems exhibit a time-dependent arrival process and can be modeled as a G(t)/GI/1 queue. Despite its wide applicability, little can be derived analytically about this system, particularly its transient behavior. Yet, many services operate on a schedule where the system is empty at the beginning and end of each day; thus, such systems are unlikely to enter a steady state. In
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A multi-objective evolutionary algorithm with mutual-information-guided improvement phase for feature selection in complex manufacturing processes Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-12-28 An-Da Li, Zhen He, Qing Wang, Yang Zhang, Yanhui Ma
Complex manufacturing processes (CMP) involve numerous features that impact product quality. Therefore, selecting key process features (KPF) is crucial for effective quality prediction and control in CMPs. This paper proposes a KPF (feature) selection method for the high-dimensional CMP data. The KPF selection problem is formulated as a bi-objective combinatorial optimization task of maximizing the
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Capacity planning of renewable energy systems using stochastic dual dynamic programming Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-12-28 J. Hole, A.B. Philpott, O. Dowson
We present a capacity expansion model for deciding the new electricity generation and transmission capacity to complement an existing hydroelectric reservoir system. The objective is to meet a forecast demand at least expected cost, namely the capital cost of the investment plus the expected discounted operating cost of the system. The optimal operating policy for any level of capacity investment can
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Opinion convergence and management: Opinion dynamics in interactive group decision-making Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-12-27 Yuan Xu, Shifeng Liu, T.C.E. Cheng, Xue Feng, Jun Wang, Xiaopu Shang
Decision-making processes are significantly influenced by internal social network interactions and external information inputs. While previous research has highlighted the role of social networks in opinion evolution, the dynamics of information dissemination and its interaction with these networks are less understood. To bridge this gap, we introduce the Social-Information-Opinion Dynamic Supernetwork
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The quadratic knapsack problem Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-12-26 Laura Galli, Silvano Martello, Paolo Toth
The quadratic knapsack problem is a relevant NP-hard combinatorial optimization problem, inspired, since the Seventies, by a number of real-world applications. After its formal definition in 1980, it was subject to intensive research, especially in the last two decades. No recent review on this problem appeared in the literature after a well-known survey, published in 2007 but updated to 2003. The
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Blockchain adoption and coordination strategies for green supply chains considering consumer privacy concern Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-12-26 Changhua Liao, Qihui Lu, Salar Ghamat, Helen Huifen Cai
Consumers’ uncertainty about the value of green products will reduce their willingness to pay, thereby obstructing green product promotion. Blockchain can eliminate this uncertainty but bring privacy concerns. We develop a game theoretical model to study a green supply chain composed of one manufacturer and one retailer, aiming to explore the implications of partial or full blockchain adoption on green
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Multi-activity shift scheduling under uncertainty: The value of shift flexibility Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-12-25 Felix Hagemann, Till Frederik Porrmann, Michael R?mer
In this paper, we consider a multi-activity shift scheduling problem under demand uncertainty, exploring various levels of flexibility in adapting aspects of the shift schedule (e.g., activity assignment, break assignment, selection of shift type and shift end time) to late-arriving demand information. To address the resulting complex two-stage stochastic combinatorial optimisation problems, we propose
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Data-driven preference learning methods for sorting problems with multiple temporal criteria Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-12-24 Yijun Li, Mengzhuo Guo, Mi?osz Kadziński, Qingpeng Zhang, Chenxi Xu
We present novel preference learning approaches for sorting problems with multiple temporal criteria. They leverage an additive value function as the basic preference model, adapted for accommodating time series data. Given assignment examples concerning reference alternatives, we learn such a model using convex quadratic programming. It is characterized by fixed-time discount factors and operates
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One Benders cut to rule all schedules in the neighbourhood Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-12-24 Ioannis Avgerinos, Ioannis Mourtos, Stavros Vatikiotis, Georgios Zois
Logic-Based Benders Decomposition (LBBD) and its Branch-and-Cut variant, namely Branch-and-Check, enjoy an extensive applicability on a broad variety of problems, including scheduling. As the application of LBBD to resource-constrained scheduling remains less explored, we propose a position-based Mixed-Integer Linear Programming (MILP) formulation for scheduling on unrelated parallel machines. To improve
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Fifty years of operational research applied to healthcare Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-12-22 Jeroen Beli?n, Sally Brailsford, Erik Demeulemeester, Derya Demirtas, Erwin W. Hans, Paul Harper
This paper gives an overview of five decades of operational research applied to healthcare, structured along nine key application domains: personnel scheduling, blood supply chain management, cancer diagnosis and treatment, emergency medical response and disaster relief, infectious diseases, long-term conditions, diagnostic imaging, public health, and operating room scheduling. Each section summarises