European Journal of Operational Research最新文献

{"title":"Anticipating Delays in Recruitment: Explainable Machine Learning for the Prediction of Hard-to-Fill Online Job Vacancies","authors":"Wouter Dossche, Sarah Vansteenkiste, Bart Baesens, Wilfried Lemahieu","doi":"10.1016/j.ejor.2025.06.027","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.06.027","url":null,"abstract":"Online job vacancy (OJV) platforms have transformed the labor market by enabling employers to advertise jobs to a wide audience. Particularly in tight labor markets, quickly identifying vacancies likely to suffer prolonged durations is crucial. This study utilizes data from the Flemish public employment service's OJV platform to examine the effectiveness of machine learning in predicting hard-to-fill vacancies. We achieve notable predictive performance with XGBoost in forecasting recruitment delays and demonstrate the importance of capturing non-linear patterns in OJV data. SHAP (SHapley Additive exPlanations) values reveal that the textual content of vacancies and latent company characteristics are key predictors of hiring delays. Counterfactual-SHAP insights provide practical guidance for refining recruitment strategies, enhancing labor market forecasts, and informing targeted policies.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"106 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144515698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy transitions under anti-environmentalism via Markov chain modeling","authors":"Simone Marsiglio, Tatyana Perevalova, Marco Tolotti","doi":"10.1016/j.ejor.2025.06.009","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.06.009","url":null,"abstract":"We analyze the effects of anti-environmentalism on the likelihood of success of the energy transition required to achieve sustainable development. We study the adoption process related to a green technology in a population formed by two sub-groups, environmentalists and anti-environmentalists, who are and are not concerned with environmental outcomes, respectively. The individual adoption decision is determined by environmental attitudes and social factors such that there exist important feedback effects within and between groups. The complexity of social dynamics and the underlying uncertainty may lead the presence of even a small group of anti-environmentalists to preclude the achievement of a green transition, especially when such agents strongly oppose the new technology or when the noise in the stochastic dynamics is sufficiently large. From a policy perspective, this implies that fighting the spread of anti-environmentalism, despite its marginal role in our society, is essential to promote a greener future.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"36 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144515702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Choice-based crowdshipping for next-day delivery services: A dynamic task display problem","authors":"Alp Arslan, Fırat Kılcı, Shih-Fen Cheng, Archan Misra","doi":"10.1016/j.ejor.2025.05.046","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.05.046","url":null,"abstract":"This paper studies integrating the crowd workforce into next-day home delivery services. In this setting, both crowd drivers and contract drivers collaborate in making deliveries. Crowd drivers have limited capacity and can choose not to deliver if the presented tasks do not align with their preferences. The central question addressed is: How can the platform minimize the total task fulfilment cost, which includes payouts to crowd drivers and additional payouts to contract drivers for delivering the unselected tasks by customizing task displays to crowd drivers? To tackle this problem, we formulate it as a finite-horizon Stochastic Decision Problem, capturing crowd drivers’ utility-driven task preferences, with the option of not choosing a task based on the displayed options. An inherent challenge is approximating the non-constant marginal cost of serving orders not chosen by crowd drivers, which are then assigned to contract drivers. We address this by leveraging a common approximation technique, dividing the service region into zones. Furthermore, we devise a stochastic look-ahead strategy that tackles the curse of dimensionality issues arising in dynamic task display execution and a non-linear (problem specifically concave) boundary condition associated with the cost of hiring contract drivers. In experiments inspired by Singapore’s geography, we demonstrate that choice-based crowd shipping can reduce next-day delivery fulfilment costs by up to 16.9%. The observed cost savings are closely tied to the task display policies and the task choice behaviours of drivers.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"89 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144515703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The continuous roll-on roll-off dual cycling problem with tugs and driver-handled cargo units","authors":"Teresa Marquardt, Arne Heinold, Catherine Cleophas, Frank Meisel","doi":"10.1016/j.ejor.2025.05.050","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.05.050","url":null,"abstract":"Roll-on roll-off vessels are a popular mode of transport in short-sea shipping. In this domain, appropriate stevedoring procedures are crucial to enhance efficiency. This includes dual cycling, where tugs simultaneously load and unload the vessel. Dual cycling reduces turnaround time, thereby giving the vessel more time to travel and allowing for slow steaming and reduced emissions.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"244 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144337654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Risk-averse contextual predictive maintenance and operations scheduling with flexible generation under wind energy uncertainty","authors":"Natalie Randall, Beste Basciftci","doi":"10.1016/j.ejor.2025.06.005","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.06.005","url":null,"abstract":"Ensuring resiliency and sustainability of power systems operations under the uncertainty of the intermittent nature of renewables is becoming a critical concern while considering the integration of flexible generation resources that provide additional adjustability during planning. To address this emerging issue, this study proposes a risk-averse contextual predictive generator maintenance and operations scheduling problem with traditional and flexible generation resources under wind energy uncertainty. We formulate this problem as a two-stage risk-averse stochastic mixed-integer program, where the first-stage determines the maintenance and unit commitment related decisions of the traditional generation units, whereas the second-stage determines the corresponding decisions for flexible generators along with the production related plans of all generators. To integrate contextual information and the uncertainty around the wind power, we propose a Gaussian Process Regression approach for predicting wind power generation, which is then leveraged into this stochastic program. Since this problem is computationally challenging to solve with a mixed-integer recourse due to the second-stage decisions involving flexible generation resources, we provide two versions of a progressive hedging based solution algorithm by first utilizing the classical progressive hedging approach and then leveraging the Frank-Wolfe algorithm for improving the solution quality. In both versions, we extend these algorithms to the risk-averse setting and present various computational enhancements. Our results on the IEEE 118-bus instances demonstrate the impact of adopting a risk-averse approach compared to risk-neutral and deterministic alternatives with a better worst-case performance, and highlight the value of integrating flexible generation and contextual information with resilient maintenance and operations schedules leading to cost-effective plans with less component failures. Furthermore, our solution algorithms provide good quality solutions in significantly less time compared to the off-the-shelf solver, where the Frank-Wolfe version of the algorithm is capable of finding optimal solutions in majority of the test instances.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"636 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144337661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nested logic-based benders decomposition for an integrated home healthcare problem","authors":"Abdalrahman Algendi, Sebastián Urrutia, Lars Magnus Hvattum, Rafael A. Melo","doi":"10.1016/j.ejor.2025.06.006","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.06.006","url":null,"abstract":"In this study, we apply nested logic-based Benders decomposition to solve an integrated home healthcare staffing, assignment, routing, and scheduling problem with application in Norway. The proposed method operates at two decomposition levels. Consequently, the entire problem is decomposed into three hierarchical sub-problems: the staffing problem, the assignment problem, and the routing and scheduling problem. These sub-problems are interrelated through two levels of logic-based Benders cuts. Computational experiments on 40 test instances demonstrate the superior performance of nested logic-based Benders decomposition compared to directly solving a mixed-integer linear programming model available in the literature. Specifically, the proposed solution method achieved proven optimality in 28 instances and provided feasible solutions for the remaining 12 instances. In contrast, directly solving the mixed-integer linear programming model yielded proven optimality in 16 instances, provided feasible solutions for 20 instances, and failed to find feasible solutions for 4 instances within the same computational time limit.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"45 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144337662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Staggered routing in autonomous mobility-on-demand systems","authors":"Antonio Coppola, Gerhard Hiermann, Dario Paccagnan, Maximilian Schiffer","doi":"10.1016/j.ejor.2025.06.008","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.06.008","url":null,"abstract":"In autonomous mobility-on-demand systems, effectively managing vehicle flows to mitigate induced congestion and ensure efficient operations is imperative for system performance and positive customer experience. Against this background, we study the potential of staggered routing, i.e., purposely delaying trip departures from a system perspective, in order to reduce congestion and ensure efficient operations while still meeting customer time windows. We formalize the underlying planning problem and show how to efficiently model it as a mixed integer linear program. Moreover, we present a matheuristic that allows us to efficiently solve large-scale real-world instances both in an offline full-information setting and its online rolling horizon counterpart. We conduct a numerical study for Manhattan, New York City, focusing on low- and highly-congested scenarios. Our results show that in low-congestion scenarios, staggering trip departures allows mitigating, on average, <mml:math altimg=\"si1.svg\" display=\"inline\"><mml:mrow><mml:mn>98</mml:mn></mml:mrow></mml:math>% of the induced congestion in a full information setting. In a rolling horizon setting, our algorithm allows us to reduce <mml:math altimg=\"si2.svg\" display=\"inline\"><mml:mrow><mml:mn>82</mml:mn></mml:mrow></mml:math>% of the induced congestion. In high-congestion scenarios, we observe an average reduction of <mml:math altimg=\"si3.svg\" display=\"inline\"><mml:mrow><mml:mn>60</mml:mn></mml:mrow></mml:math>% as the full information bound and an average reduction of <mml:math altimg=\"si4.svg\" display=\"inline\"><mml:mrow><mml:mn>30</mml:mn></mml:mrow></mml:math>% in our online setting. Surprisingly, we show that these reductions can be reached by shifting trip departures by a maximum of six minutes in both the low and high-congestion scenarios.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"15 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144337663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How live-streaming commerce interacts with two-period pricing when selling to strategic customers","authors":"Pingping Chen, Lei Xie, Lu Dai, Zhuzhu Song","doi":"10.1016/j.ejor.2025.05.042","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.05.042","url":null,"abstract":"Live-streaming commerce serves as a novel marketing tool in the digital era, facilitating real-time interactions between streamers and customers to enhance product sales. However, the transition back to solely traditional online channels following live-stream events presents decision-making challenges for firms regarding dynamic pricing, price commitment, and price matching schemes, particularly when dealing with strategic customers. We develop a two-period theoretical model to explore the selection of pricing schemes by a firm who may launch a live-streaming sales. Our analysis reveals that while live-streaming cannot necessarily enhance profitability under price commitment scheme, it significantly boosts profits under dynamic pricing and price matching schemes due to amplified pricing flexibility. The increased customer patience in strategic waiting diminishes the benefits of live-streaming under dynamic pricing, whereas it enhances them under price matching with reimbursement mechanisms. Moreover, dynamic pricing and price matching schemes, traditionally perceived as less favorable, emerge as potentially more effective due to the real-time value enhancement effect of live-streaming commerce, which can mitigate customers’ strategic delay in purchasing decisions. The firm’s selection of an optimal pricing scheme under live-streaming commerce can also maximize consumer surplus, thereby enhancing social welfare and promoting a positive image of corporate social responsibility advocated by governmental bodies. This “win-win-win” scenario for the firm, customers, and government can be achieved through dynamic pricing or price commitment schemes. In this context, a conducive social environment can be fostered, enabling all participants to collaborate in expanding opportunities and benefiting everyone.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"3 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144337666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nonconvex truncated conditional value at risk-based sparse linear regression","authors":"Boyi Xie, Zhongming Wu, Min Li","doi":"10.1016/j.ejor.2025.06.004","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.06.004","url":null,"abstract":"Conditional value at risk (CVaR) is a widely recognized risk measure used to manage data uncertainty within risk management. In this paper, we study a class of sparse linear regression models based on truncated CVaR measure and <mml:math altimg=\"si1.svg\" display=\"inline\"><mml:msub><mml:mrow><mml:mi>ℓ</mml:mi></mml:mrow><mml:mrow><mml:mn>0</mml:mn></mml:mrow></mml:msub></mml:math>-norm regularization. Due to the nonconvexity and nonsmoothness of the objective functions, as well as the NP-hardness of the problem with the <mml:math altimg=\"si1.svg\" display=\"inline\"><mml:msub><mml:mrow><mml:mi>ℓ</mml:mi></mml:mrow><mml:mrow><mml:mn>0</mml:mn></mml:mrow></mml:msub></mml:math>-norm regularization, we propose an approximation model that employs a tight relaxation of the <mml:math altimg=\"si1.svg\" display=\"inline\"><mml:msub><mml:mrow><mml:mi>ℓ</mml:mi></mml:mrow><mml:mrow><mml:mn>0</mml:mn></mml:mrow></mml:msub></mml:math>-norm. The solution equivalence between the proposed model and its approximation model is explored. To efficiently solve the approximation model, we develop a semismooth Newton-based proximal majorization-minimization algorithm. Furthermore, the convergence analysis of the proposed algorithm is presented, and the convergence rate for the reduced CVaR-based sparse linear regression model is established. Moreover, extensive numerical experiments conducted on both synthetic and real datasets validate the stability and effectiveness of the proposed algorithm, demonstrating significant improvements in both sparsity and accuracy compared to existing state-of-the-art methods.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"99 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144337620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Project monitoring and control with an empirically grounded budget-release model","authors":"Jie Song, Jinbo Song, Tyson Browning, Mario Vanhoucke","doi":"10.1016/j.ejor.2025.06.007","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.06.007","url":null,"abstract":"Project monitoring and control (PMC) is a process of measuring a project’s progress and taking corrective action when necessary to ensure successful project completion. However, most existing models lack empirical validation of their assumptions and effectiveness, which limits their practical use. We fill in this gap by using empirical data from 97 real projects to calibrate activity-duration distributions and assess activity-duration dependencies, integrating these empirical foundations into an enhanced PMC model. We further improve the model by incorporating budget-release timing constraints and introducing two new policies for crashing and fast-tracking based on a project’s specific time and cost characteristics. Extensive computational experiments using empirical and artificial data evaluate the effectiveness of these policies. Because the budget-release policies and corrective action types depend on project characteristics such as activity-duration dependencies and topological network structure, key insights from this study can be usefully applied by project managers as heuristics even without a detailed model of their project.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"17 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144337664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}