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Simple fixes that accommodate switching costs in multi-armed bandits Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-19 Ehsan Teymourian, Jian Yang
When switching costs are added to the multi-armed bandit (MAB) problem where the arms’ random reward distributions are previously unknown, usually quite different techniques than those for pure MAB are required. We find that two simple fixes on the existing upper-confidence-bound (UCB) policy can work well for MAB with switching costs (MAB-SC). Two cases should be distinguished. One is with positive-gap
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Probabilistic branch and bound considering stochastic constraints Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-17 Hao Huang, Shing Chih Tsai, Chuljin Park
In this paper, we investigate a simulation optimization problem that poses challenges due to (i) the inability to evaluate the objective and multiple constraint functions analytically; instead, we rely on stochastic simulation to estimate them, and (ii) a discrete and potentially vast solution space. Rather than providing a single optimal solution, our aim is to identify a set of near-optimal solutions
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Mathematical models based on decision hypergraphs for designing a storage cabinet Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-16 Luis Marques, François Clautiaux, Aurélien Froger
We study the problem of designing a cabinet made up of a set of shelves that contain compartments whose contents slide forward on opening. Considering a set of items candidate to be stored in the cabinet over a given time horizon, the problem is to design a set of shelves and a set of compartments on each shelf, and select the items to insert into the compartments. The objective is to maximize the
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Attention-based dynamic multilayer graph neural networks for loan default prediction Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-14 Sahab Zandi, Kamesh Korangi, María Óskarsdóttir, Christophe Mues, Cristián Bravo
Whereas traditional credit scoring tends to employ only individual borrower- or loan-level predictors, it has been acknowledged for some time that connections between borrowers may result in default risk propagating over a network. In this paper, we present a model for credit risk assessment leveraging a dynamic multilayer network built from a Graph Neural Network and a Recurrent Neural Network, each
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An indifference result for social choice rules in large societies Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-12 Dezső Bednay, Balázs Fleiner, Attila Tasnádi
Social choice rules can be defined or derived by minimizing distance-based objective functions. One problem with this approach is that any social choice rule can be derived by selecting an appropriate distance function. Another problem comes from the computational difficulty of determining the solution of some social choice rules. We provide a general positive indifference result when looking at expected
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Condition-based switching, loading, and age-based maintenance policies for standby systems Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-10 Xian Zhao, Rong Li, He Han, Qingan Qiu
Standby techniques are widely incorporated in structural design to enhance the inherent reliability of systems. To further leverage the system performance during operation, decision-makers can adopt operational policies to manage system degradation. Specifically, at the system level, unit switching that dynamically determines the online unit contributes to avoiding unexpected shutdowns. At the unit
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A newsvendor model with multiple reference points: Target-setting for aspirational newsvendors Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-10 Tian Bai, Gengzhong Feng, Meng Wu, Stuart X. Zhu
Prospect theory posits that the determination of an outcome as a gain or loss hinges upon the reference points, thereby exerting a substantial influence on the decision-making processes of individuals. These reference points can encompass both external targets and internal aspirations (self-goals), forming two potential candidates. Despite a growing body of evidence showcasing the concurrent impact
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App release strategy in the presence of competitive platforms’ quality upgrades Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-07 Xiangxiang Wu, Yong Zha
Mobile platforms such as Google Android and Apple iOS have established their app stores to entice numerous app developers into their platform ecosystem. These platform firms will deliberate on upgrading the quality of their platforms to bolster performance and security, while app developers may choose to rely on different platforms to release their developed apps as a strategic response. In this study
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Overseas production or domestic production? Impacts of tax disparity and market difference Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-07 Baozhuang Niu, Nan Zhang, Zihao Mu
Overseas and domestic production are two commonly employed strategies for multinational firms (MNFs) to manage their global production operations. Recent tax-cutting initiatives have made domestic production an attractive option for MNFs. We aim to investigate whether such initiatives can effectively induce MNFs to produce domestically, especially when they cater to both domestic and foreign markets
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Equilibrium analysis of the seller’s fulfillment channels and sales channels Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-07 Shu Hu, Ke Fu
Sellers’ products can be sold either through platform channels or through their own channels. Also, sellers’ orders can either be fulfilled by platforms (FBP) or be fulfilled by third-party merchants (FBM). We consider a platform and a representative seller that compete in selling two substitutable products. We develop an analytical framework for identifying each firm’s structure preference by comparing
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Adaptive robust online portfolio selection Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-06 Man Yiu Tsang, Tony Sit, Hoi Ying Wong
The online portfolio selection (OLPS) problem differs from classical portfolio model problems, as it involves making sequential investment decisions. Many OLPS strategies described in the literature capture market movement based on various beliefs and are shown to be profitable. In this paper, we propose a robust optimization (RO)-based strategy that takes transaction costs into account. Moreover,
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A fused large language model for predicting startup success Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-06 Abdurahman Maarouf, Stefan Feuerriegel, Nicolas Pröllochs
Investors are continuously seeking profitable investment opportunities in startups and, hence, for effective decision-making, need to predict a startup’s probability of success. Nowadays, investors can use not only various fundamental information about a startup (e.g., the age of the startup, the number of founders, and the business sector) but also textual description of a startup’s innovation and
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Retailer’s information sharing and manufacturer’s channel expansion in the live-streaming E-commerce era Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-06 Wei Lu, Xiang Ji, Jie Wu
Numerous manufacturers started to embrace live-streaming selling channels in addition to their preexisting retail channels during the outbreak of COVID-19. Our work investigates a retailer’s optimal strategy for sharing demand information with a manufacturer who may collaborate with a streamer to build a live-streaming selling channel. The results indicate that the manufacturer’s live-streaming selling
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Addressing the multiplicity of optimal solutions to the Clonal Deconvolution and Evolution Problem Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-06 Maitena Tellaetxe-Abete, Charles Lawrie, Borja Calvo
The Clonal Deconvolution and Evolution Problem consists on unraveling the clonal structure and phylogeny of a tumor using estimated mutation frequency values obtained from multiple biopsies containing mixtures of tumor clones. In this article, we tackle the problem from an optimization perspective and we explore the number of optimal solutions for a given instance. Even in ideal scenarios without noise
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Moderate exponential-time quantum dynamic programming across the subsets for scheduling problems Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-05 Camille Grange, Michael Poss, Eric Bourreau, Vincent T’kindt, Olivier Ploton
Grover Search is currently one of the main quantum algorithms leading to hybrid quantum–classical methods that reduce the worst-case time complexity for some combinatorial optimization problems. Specifically, the combination of Quantum Minimum Finding (obtained from Grover Search) with dynamic programming has proved particularly efficient in improving the complexity of NP-hard problems currently solved
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Quadratic horizontally elastic not-first/not-last filtering algorithm for cumulative constraint Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-03 Roger Kameugne, Sévérine Fetgo Betmbe, Thierry Noulamo
The not-first/not-last rule is a pendant of the edge finding rule, generally embedded in the constraint during constraint-based scheduling. It is combined with other filtering rules for more pruning of the tree search. In this paper, the data structure in which tasks are scheduled in a horizontally elastic way is used to strengthen the classic not-first/not-last rule. Potential not-first task intervals
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Measures of stochastic non-dominance in portfolio optimization Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-03 Jana Junová, Miloš Kopa
Stochastic dominance rules are well-characterized and widely used. This work aims to describe and better understand the situations when they do not hold by developing measures of stochastic non-dominance. They quantify the error caused by assuming that one random variable dominates another one when it does not. To calculate them, we search for a hypothetical random variable that satisfies the stochastic
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End-to-end, decision-based, cardinality-constrained portfolio optimization Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-09-02 Hassan T. Anis, Roy H. Kwon
Portfolios employing a (factor) risk model are usually constructed using a two step process: first, the risk model parameters are estimated, then the portfolio is constructed. Recent works have shown that this decoupled approach may be improved using an integrated framework that takes the downstream portfolio optimization into account during parameter estimation. In this work we implement an integrated
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Explainable profit-driven hotel booking cancellation prediction based on heterogeneous stacking-based ensemble classification Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-31 Zhenkun Liu, Koen W. De Bock, Lifang Zhang
The goal of hotel booking cancellation prediction in the hospitality industry is to identify potential cancellations from a large customer base and improve the efficiency of customer retention and capacity management efforts. Whilst prior research has shown that the predictive performance of hotel booking cancellation prediction can be further enhanced by integrating multiple classifiers, the explainability
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Industry return prediction via interpretable deep learning Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-31 Lazaros Zografopoulos, Maria Chiara Iannino, Ioannis Psaradellis, Georgios Sermpinis
We apply an interpretable machine learning model, the LassoNet, to forecast and trade U.S. industry portfolio returns. The model combines a regularization mechanism with a neural network architecture. A cooperative game-theoretic algorithm is also applied to interpret our findings. The latter hierarchizes the covariates based on their contribution to the overall model performance. Our findings reveal
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Integration of prediction and optimization for smart stock portfolio selection Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-30 Puja Sarkar, Vivekanand B. Khanapuri, Manoj Kumar Tiwari
Machine learning (ML) algorithms pose significant challenges in predicting unknown parameters for optimization models in decision-making scenarios. Conventionally, prediction models are optimized independently in decision-making processes, whereas ML algorithms primarily focus on minimizing prediction errors, neglecting the role of decision-making in downstream optimization tasks. The pursuit of high
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Asymptotically optimal energy consumption and inventory control in a make-to-stock manufacturing system Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-28 Erhun Özkan, Barış Tan
We study a make-to-stock manufacturing system in which a single server makes the production. The server consumes energy, and its power consumption depends on the server state: a busy server consumes more power than an idle server, and an idle server consumes more power than a turned-off server. When a server is turned on, it completes a costly set-up process that lasts a while. We jointly control the
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An optimization framework for solving large scale multidemand multidimensional knapsack problem instances employing a novel core identification heuristic Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-28 Sameh Al-Shihabi
By applying the core concept to solve a binary integer program (BIP), certain variables of the BIP are fixed to their anticipated values in the optimal solution. In contrast, the remaining variables, called core variables, are used to construct and solve a core problem (CP) instead of the BIP. A new approach for identifying CP utilizing a local branching (LB) alike constraint is presented in this article
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Multiple financial analyst opinions aggregation based on uncertainty-aware quality evaluation Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-28 Shuai Jiang, Wenjun Zhou, Yanhong Guo, Hui Xiong
Financial analysts’ opinions are pivotal in investment decision-making, as they provide valuable expert knowledge. Aggregating these opinions offers a promising way to unlock their collective wisdom. However, existing opinion aggregation methods are hindered by their inability to effectively assess differences in opinion quality, resulting in suboptimal outcomes. This Study introduces a novel model
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The circular balancing problem Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-24 Myungho Lee, Kangbok Lee, Michael Pinedo
We propose a balancing problem with a minmax objective in a circular setting. This balancing problem involves the arrangement of an even number of items with different weights on a circle while minimizing the maximum total weight of items arranged on any half circle. Due to its generic structure, it may have applications in fair resource allocation schemes. We show the NP-hardness of the problem and
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Fair integer programming under dichotomous and cardinal preferences Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-24 Tom Demeulemeester, Dries Goossens, Ben Hermans, Roel Leus
One cannot make truly fair decisions using integer linear programs unless one controls the selection probabilities of the (possibly many) optimal solutions. For this purpose, we propose a unified framework when binary decision variables represent agents with preferences, who only care about whether they are selected in the final solution. We develop several general-purpose algorithms to fairly select
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A multiobjective [formula omitted]-constraint based approach for the robust master surgical schedule under multiple uncertainties Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-23 Salma Makboul, Alexandru-Liviu Olteanu, Marc Sevaux
The efficient scheduling of elective surgeries in hospitals is critical for ensuring patient satisfaction, cost-effectiveness, and overall operational efficiency. However, operating theater (OT) managers face complex and competing scheduling problems due to numerous sources of uncertainty and the impact of the proposed schedule on downstream recovery units, such as the intensive care unit (ICU). To
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Evaluation of counterparty credit risk under netting agreements Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-23 Ahmadreza Tavasoli, Michèle Breton
We investigate counterparty credit risk and credit valuation adjustments in portfolios including derivatives with early-exercise opportunities, under a netting agreement. We show that credit risk and netting agreements have a significant impact on the way portfolios are managed (that is, on options’ exercise strategies) and, therefore, on the value of the portfolio and on the price of counterparty
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Maintenance optimization for multi-component systems with a single sensor Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-22 Ragnar Eggertsson, Ayse Sena Eruguz, Rob Basten, Lisa M. Maillart
We consider a multi-component system in which a single sensor monitors a condition parameter. Monitoring gives the decision maker partial information about the system state, but it does not reveal the exact state of the components. Each component follows a discrete degradation process, possibly correlated with the degradation of other components. The decision maker infers a belief about each component’s
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A framework for integrated resource planning in surgical clinics Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-22 Thomas Reiten Bovim, Anders N. Gullhav, Henrik Andersson, Atle Riise
The problem under study is based on the challenges faced by the Orthopaedic Clinic at St. Olav’s Hospital in Trondheim, Norway. Variations in demand and supply cause fluctuating waiting lists, and it is challenging to level the activities between the clinic’s two units, the outpatient clinic and the operating theater, to obtain short waiting times for all activities. Based on these challenges, we describe
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Applying fixed order commitment contracts in a capacitated supply chain Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-22 Christina Imdahl, Kai Hoberg, William Schmidt
Demand uncertainty can lead to excess inventory holdings, capacity creation, emergency deliveries, and stock-outs. The costs of demand uncertainty may be directly borne by upstream suppliers, but can propagate downstream in the form of higher prices. To address these problems, we investigate a practical application of a fixed order commitment contract (FOCC) in which a manufacturer commits to a minimum
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Portfolio default losses driven by idiosyncratic risks Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-21 Shaoying Chen, Zhiwei Tong, Yang Yang
We consider a portfolio of general defaultable assets with low individual default risk and study the probability of the portfolio default loss exceeding an arbitrary threshold. The latent variables driving defaults are modeled by a mixture structure that combines common shock, systematic risk, and idiosyncratic risk factors. While common shocks and systematic risk have been found by many studies to
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Exact and heuristic approaches for the ship-to-shore problem Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-19 M. Wagenvoort, P.C. Bouman, M. van Ee, T. Lamballais Tessensohn, K. Postek
After a natural disaster such as a hurricane or flooding, the navy can help by bringing supplies, clearing roads, and evacuating victims. If destinations cannot be reached over land, resources can be transported using smaller ships and helicopters, called connectors. To start aid on land as soon as possible this must be done efficiently. In the ship-to-shore problem, trips with their accompanying resources
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Customer and provider bounded rationality in on-demand service platforms Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-17 Danna Chen, Yong-Wu Zhou, Xiaogang Lin, Kangning Jin
The growing literature on operations management in the context of the sharing economy typically assumes that both customers and providers are fully rational. In contrast, we consider an on-demand service platform (e.g., Didi and Uber) with boundedly rational customers and providers that sets a price charged to customers and a wage paid to providers. Both customers and providers are sensitive to the
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Optimal payoffs under smooth ambiguity Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-17 An Chen, Steven Vanduffel, Morten Wilke
We study optimal payoff choice for an investor in a one-period model under smooth ambiguity preferences, also called as proposed by Klibanoff et al. (2005). In contrast to the existing literature on optimal asset allocation for a KMM investor in a one-period model, we also allow payoffs that are non-linear in the market asset. Our contribution is fourfold. First, we characterize and derive the optimal
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Corrigendum to “Labeling methods for partially ordered paths” [European Journal of Operational Research 318 (2024) 19–30] Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-16 Ricardo Euler, Pedro Maristany de las Casas
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An unified framework for measuring environmentally-adjusted productivity change: Theoretical basis and empirical illustration Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-14 A. Abad, P. Ravelojaona
This paper aims to define an unified framework to analyse environmentally-adjusted productivity change. Equivalence conditions for additive and multiplicative environmentally-adjusted productivity indicators and indices are highlighted. Besides, an empirical illustration is provided considering non parametric convex neutral by-production model.
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Optimizing omnichannel retailer inventory replenishment using vehicle capacity-sharing with demand uncertainties and service level requirements Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-13 Ruozhen Qiu, Mingli Yuan, Minghe Sun, Zhi-Ping Fan, Henry Xu
This study explores an inventory replenishment problem for an omnichannel retailer selling a product with demand uncertainties and service level requirements in different channels through a capacity-sharing strategy. The omnichannel retailer allows customers to order products online and then pick them up in retail stores. The capacity-sharing strategy is considered to reduce travel costs when the omnichannel
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Bilinear branch and check for unspecified parallel machine scheduling with shift consideration Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-13 Ponpot Jartnillaphand, Elham Mardaneh, Hoa T. Bui
This paper tackles the complex challenge of team formations, assignments, and job schedules within the static Unspecified Parallel Machine Flexible Resource Scheduling problem, specifically incorporating shift considerations. In existing literature, teams are often simplified as machines that operate continuously throughout the day without any interruptions. However, in reality, teams require breaks
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A unified solution framework for flexible job shop scheduling problems with multiple resource constraints Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-12 Gregory A. Kasapidis, Dimitris C. Paraskevopoulos, Ioannis Mourtos, Panagiotis P. Repoussis
This paper examines flexible job shop scheduling problems with multiple resource constraints. A unified solution framework is presented for modelling various types of non-renewable, renewable and cumulative resources, such as limited capacity machine buffers, tools, utilities and work in progress buffers. We propose a Constraint Programming (CP) model and a CP-based Adaptive Large Neighbourhood Search
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Integrated crew organization and work zone scheduling for network-wide daily road pavement rehabilitation Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-12 Wenyi Zhang, Yanbo He, Xuan Zhang, Tao Liu, Wei Guan
This study develops a new integer-programming model to address the network-wide daily road pavement rehabilitation scheduling problem. In the model, the crew organization and work zone schedule are jointly optimized daily, with the objective of minimizing both the operational cost and user travel time. A day-to-day traffic dynamics model is applied to capture the non-equilibrium traffic evolution against
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On indication, strict monotonicity, and efficiency of projections in a general class of path-based data envelopment analysis models Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-12 Margaréta Halická, Mária Trnovská, Aleš Černý
Data envelopment analysis (DEA) theory formulates a number of desirable properties that DEA models should satisfy. Among these, indication, strict monotonicity, and strong efficiency of projections tend to be grouped together in the sense that, in individual models, typically, either all three are satisfied or all three fail at the same time. Specifically, in slacks-based graph models, the three properties
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Bounds and heuristic algorithms for the bin packing problem with minimum color fragmentation Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-06 Mathijs Barkel, Maxence Delorme, Enrico Malaguti, Michele Monaci
In this paper, we consider a recently introduced packing problem in which a given set of weighted items with colors has to be packed into a set of identical bins, while respecting capacity constraints and the number of available bins, and minimizing the total number of times that colors appear in the bins. We review exact methods from the literature and present a fast lower bounding procedure that
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A value-at-risk based approach to the routing problem of multi-hazmat railcars Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-06 Kan Fang, Enyuan Fu, Dian Huang, Ginger Y. Ke, Manish Verma
This paper solves a routing problem of multi-hazmat railcars with consolidation operations in order to avoid serious consequences of hazmat accidents. We develop a bi-level optimization model for this problem, and apply a value-at-risk (VaR) approach to generate route choices. By incorporating the consolidation operations performed among different railway shipments, both the risks incurred at yards
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Agency selling or reselling: The role of cause marketing Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-05 Lin Wei, Shengming Zheng, Shaofu Du, Baofeng Zhang
Cause marketing (CM) is commonly adopted to pursue profit growth or/and achieve corporate social responsibility (CSR). In online retailing, to facilitate CM for the products, e-retailers are increasingly implementing CM programs for the firms that sell products directly to consumers, i.e., suppliers under agency selling mode or themselves under reselling mode. Motivated by this, we examine how CM for
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Optimizing integrated berth allocation and quay crane assignment: A distributionally robust approach Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-05 Chong Wang, Qi Wang, Xi Xiang, Canrong Zhang, Lixin Miao
In this research, we have formulated a Two-Stage Distributionally Robust Optimization (TDRO) model within the context of a mean–variance ambiguity set, specifically designed to address the challenges in the Integrated Berth Allocation and Quay Crane Assignment Problem (BACAP). A key consideration in this study is the inherent uncertainty associated with ships’ arrival times. During the initial stage
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Physical vs Virtual corporate power purchase agreements: Meeting renewable targets amid demand and price uncertainty Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-03 Seyed Danial Mohseni Taheri, Selvaprabu Nadarajah, Alessio Trivella
Power purchase agreements (PPAs) have become an important corporate procurement vehicle for renewable power, especially among companies that have committed to targets requiring a certain fraction of their power demand be met by renewables. PPAs are long-term contracts that provide renewable energy certificates (RECs) to the corporate buyer and take two main forms: Physical vs Virtual. Physical PPAs
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Surgery scheduling in flexible operating rooms by using a convex surrogate model of second-stage costs Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-02 Mohammed Majthoub Almoghrabi, Guillaume Sagnol
We study the elective surgery planning problem in a hospital with operating rooms shared by elective and emergency patients. This problem is split in two distinct phases. First, a subset of patients to be operated in the next planning period is selected and the selected patients are assigned to a block and a tentative starting time. Then, in the online phase of the problem, a policy decides how to
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Industrial multi-resource flexible job shop scheduling with partially necessary resources Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-02 Quentin Perrachon, Alexandru-Liviu Olteanu, Marc Sevaux, Sylvain Fréchengues, Jean-François Kerviche
This paper is dedicated to the study of industrial extensions of the flexible job shop scheduling problem with multiple resources in order to propose an alternative to expensive optimization software for small to medium-sized manufacturing companies. In this context, we propose a generic model able to tackle some constraints often found in industrial scheduling problems. This model tackles partially
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Time-to-build, regulation, and investment Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-02 Haejun Jeon
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Generating sets of diverse and plausible scenarios through approximated multivariate normal distributions Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-08-02 Eljas Aalto, Tuomo Kuosa, Max Stucki
This article presents a novel and broadly generalizable framework for generating diverse and plausible sets of scenarios. Potential future outcomes are decomposed using a set of uncertainties which are assumed to be multivariate normally distributed, regardless of whether the uncertainties actually present numerically quantifiable phenomena. The optimal scenarios are then chosen along the principal
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Globally optimal sequencing of optimal reactive dispatch control adjustments to minimize operational losses in transmission systems by graph shortest path, parallel computing, and dynamic programming Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-07-31 Rafael Martins Barros, Guilherme Guimarães Lage, Ricardo de Andrade Lira Rabêlo
Minimizing operational losses in transmission systems through the Optimal Reactive Dispatch (ORD), a non-convex mixed-integer nonlinear programming problem, is crucial for operational cost reduction, resource optimization, and greenhouse gas emission mitigation. Besides all intricacies associated with solving ORDs, transmission system operators encounter the challenge of determining sequences in which
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A restless bandit model for dynamic ride matching with reneging travelers Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-07-31 Jing Fu, Lele Zhang, Zhiyuan Liu
This paper studies a large-scale ride-matching problem with a large number of travelers who are either drivers with vehicles or riders looking for sharing vehicles. Drivers can match riders that have similar itineraries and share the same vehicle; and reneging travelers, who become impatient and leave the service system after waiting a long time for shared rides, are considered in our model. The aim
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Cost efficiency in water supply systems: An applied review on optimization models for the pump scheduling problem Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-07-31 Marlene Brás, Ana Moura, António Andrade-Campos
The need for efficient pump operation in water supply systems (WSS) has become increasingly important over time, driven by the growing energy consumption and the associated energy costs. Forecasts for 2050 anticipate a global increase in water demand by 55%, indicating an increasing surge in WSS energy consumption. Control of pumping stations, which consume 70% of the energy in WSS, is the most critical
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Fifty years of multiple criteria decision analysis: From classical methods to robust ordinal regression Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-07-30 Salvatore Greco, Roman Słowiński, Jyrki Wallenius
Multiple Criteria Decision Analysis (MCDA) is a subfield of Operational Research that aims to support Decision-Makers (DMs) in the decision-making process through mathematical models and computational procedures. In this perspective, MCDA employs structured and traceable protocols to identify potential actions and the criteria for evaluating them. MCDA procedures aim to define recommendations consistent
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Managing oversaturation in BRT corridors: A new approach of timetabling for resilience enhancement using a tailored integer L-shaped algorithm Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-07-30 Yiran Wang, Pengli Mo, Jingxu Chen, Zhiyuan Liu
Bus rapid transit (BRT) is a high-capacity public transport system that typically operates along urban transit corridors with dense travel demand. Maintaining the efficiency and stability of the BRT is paramount for daily transport operations. Owing to the difficulty in ensuring an exclusive right-of-way along the entire route, stochastic congestion events may occur resulting from road segments without
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The impact of the correlation coefficient of interarrival and service times on queueing performance: The [formula omitted] case Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-07-30 Haoran Wu, Qi-Ming He, Li Xia
This paper is concerned on an queue with correlated interarrival and service times. In particular, we assume that the interarrival time and service time of a customer have a bivariate exponential distribution. By utilizing a Markov modulated fluid flow (MMFF) process associated with the age process of the customer in service, we obtain a number of queueing quantities in closed form. Using the solutions
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Decision-focused neural adaptive search and diving for optimizing mining complexes Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-07-27 Yassine Yaakoubi, Roussos Dimitrakopoulos
Optimizing industrial mining complexes, from extraction to end-product delivery, presents a significant challenge due to non-linear aspects and uncertainties inherent in mining operations. The two-stage stochastic integer program for optimizing mining complexes under joint supply and demand uncertainties leads to a formulation with tens of millions of variables and non-linear constraints, thereby challenging
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Alleviating poverty for common prosperity: The role of Fupinguan in an E-tailing supply chain Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-07-27 Qingyu Zhang, Yuting Liang, Maosen Zhou
To alleviate poverty, e-tailers in China have established special web portals or channels, known as Fupinguans (FPGs), to sell products from poor suppliers in rural areas. This paper investigates the underlying mechanism of FPGs in poverty alleviation (PA) and explores their implications for the common prosperity of stakeholders. We consider an e-tailing supply chain where an e-tailer sells substitutes
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A matheuristic with re-lot-sizing strategies for flexible job-shop rescheduling problem with lot-streaming and machine reconfigurations Eur. J. Oper. Res. (IF 6.0) Pub Date : 2024-07-27 Jiaxin Fan, Chunjiang Zhang, Fajun Yang, Weiming Shen, Liang Gao
This paper investigates a flexible job-shop rescheduling problem with lot-streaming and machine reconfigurations (FJRP-LSMR) for the total weighted tardiness minimization, where production setups between sublots are performed by assembling selected auxiliary modules to reconfigure machines. When a given long-term schedule is interrupted by dynamic events, such as machine breakdowns and job insertions