European Journal of Operational Research最新文献_第3页

A jump–diffusion Stackelberg stochastic differential game in optimal carbon abatement strategies with green subsidy 考虑绿色补贴的最优碳减排策略的跳跃-扩散Stackelberg随机微分对策

IF 6 2区管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

European Journal of Operational Research

Pub Date : 2026-05-16 Epub Date: 2025-09-28 DOI: 10.1016/j.ejor.2025.09.035

Yuhan Li , Xiaoshan Su , Jiandong Wang , Haijun Yang

The increasingly severe challenges of global warming necessitate a low-carbon transition that involves quantified estimation of carbon emission reduction policies. Carbon trading with abatement subsidization has proven to be an effective measure for evaluating the social cost of carbon emissions. However, conflicting targets between the government and firms can cause principal–agent issues in reducing carbon dioxide emissions. We propose a novel Itô–Lévy jump–diffusion state equation to depict the dramatic fluctuations of carbon prices, a critical factor in carbon trading. To analyze the complex game behaviors in carbon abatement, we construct a multiple players Stackelberg stochastic differential game model applying stochastic optimal control theory in principal–agent situations. Our model examines the incentive compatibility mechanism while considering the complex behaviors of carbon trading participants with asymmetric information. Optimal feedback control strategies are explicitly presented for the government and firms to achieve their separate targets of maximizing social welfare and production profits. Green subsidization coupled with carbon quotas trading is a viable option for promoting carbon abatement. However, high-carbon firms may attempt to deceive the government by pretending to be low-carbon ones. We illustrate that carbon traders with deceptive intentions lead to negative social welfare and hinder carbon abatement achievements.

全球变暖带来的日益严峻的挑战要求向低碳转型，这需要对碳减排政策进行量化评估。碳交易与减排补贴已被证明是评估碳排放社会成本的有效手段。然而，政府和企业之间的目标冲突会导致减少二氧化碳排放的委托代理问题。我们提出了一个新的Itô-Lévy跳跃-扩散状态方程来描述碳价格的剧烈波动，这是碳交易的一个关键因素。为了分析碳减排中的复杂博弈行为，应用随机最优控制理论，构建了委托代理情况下的多参与者Stackelberg随机微分博弈模型。该模型在考虑信息不对称的碳交易参与者复杂行为的情况下，考察了激励相容机制。明确提出了政府和企业实现社会福利最大化和生产利润最大化目标的最优反馈控制策略。绿色补贴与碳配额交易相结合是促进碳减排的可行选择。然而，高碳企业可能试图通过伪装成低碳企业来欺骗政府。我们论证了具有欺骗性意图的碳交易者会导致负面的社会福利，阻碍碳减排的成就。

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引用次数: 0

Advances in multi-crane scheduling: Extended non-interference modeling and temporal-constraint-based valid inequalities 多起重机调度研究进展：扩展无干扰建模和基于时间约束的有效不等式

IF 6 2区管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

European Journal of Operational Research

Pub Date : 2026-05-16 Epub Date: 2025-10-25 DOI: 10.1016/j.ejor.2025.10.032

Woo-Jin Shin, Hyun-Jung Kim

This study investigates the multi-crane scheduling problem (MCSP), motivated by operational challenges at a steelmaking plant in South Korea. In this problem, multiple cranes operate on tracks and perform tasks involving the transportation of materials between production machines. A key challenge in the MCSP is avoiding interference between cranes that share tracks. While an existing closed-form non-interference model is available, it applies only to scenarios where cranes remain stationary while executing tasks-such as quay cranes in container terminals. This research significantly extends that model to accommodate tasks in which cranes transport materials across multiple locations on tracks, enabling more efficient modeling and analysis for broader variants of the MCSP. In addition, we address temporal constraints (TCs), including both time windows for task start times and generalized precedence relations among tasks, which arise from pre-scheduled production plans. To solve the MCSP with TCs, we propose a novel mixed-integer linear programming (MILP) formulation that minimizes the total flow time of tasks, based on the extended non-interference model. We further enhance the MILP by incorporating valid inequalities derived from network analysis on TCs. The effectiveness of our methods is validated through comparisons with existing MILPs using real-world data from the investigated plant.

本研究以韩国一家炼钢厂为研究对象，探讨了多起重机调度问题（MCSP）。在这个问题中，多个起重机在轨道上运行，并执行涉及在生产机器之间运输材料的任务。MCSP的一个关键挑战是避免共享轨道的起重机之间的干扰。虽然现有的封闭式非干扰模型可用，但它仅适用于起重机在执行任务时保持静止的场景，例如集装箱码头的码头起重机。这项研究极大地扩展了该模型，以适应起重机在轨道上跨多个位置运输材料的任务，从而为更广泛的MCSP变体提供更有效的建模和分析。此外，我们还解决了时间约束（tc），包括任务开始时间的时间窗口和任务之间的广义优先关系，这些都是由预先安排的生产计划引起的。为了解决具有tc的MCSP问题，我们提出了一种新的混合整数线性规划（MILP）公式，该公式基于扩展的无干扰模型，使任务的总流时间最小化。我们通过结合从tc的网络分析中得到的有效不等式进一步增强了MILP。我们的方法的有效性是通过与现有的milp使用来自被调查工厂的真实世界数据进行比较来验证的。

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引用次数: 0

Quantile-adaptive probabilistic forecast combining 分位数-自适应概率预测组合

IF 6 2区管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

European Journal of Operational Research

Pub Date : 2026-05-01 Epub Date: 2025-12-03 DOI: 10.1016/j.ejor.2025.11.031

Ke Yu , James W. Taylor , Xiaochun Meng

Combining forecasts of cumulative probability distributions (CDFs) allows aggregation of the available information to improve accuracy. The linear opinion pool is commonly used, but it can yield overdispersed distributional forecasts. An alternative, leading to lower dispersion, is to average the quantiles of the CDF, which can be viewed as horizontal CDF averaging, with the averaging of probabilities in the linear opinion pool viewed as vertical averaging. Empirical results show that horizontal and vertical averaging can each be preferable for different parts of the CDF. For example, one method might be better for tail quantiles, while the other is better for central quantiles. To address this, we develop a method that transitions between vertical and horizontal averaging across the CDF. It relates to angular averaging, which is a recent proposal that performs aggregation along lines at an angle. Our new method averages along lines with slopes that smoothly transition across the CDF. The method is quantile-adaptive in the sense that the slopes of the lines vary across the quantiles, or equivalently, across the probabilities. We set the lines to emanate from a small number of fixed points, which are the parameters of the method. Viewing the lines as rays, we term the method radial averaging. Our theoretical results show that the method has the versatility to generate CDF forecasts that are sharper than horizontal averaging, and less sharp than vertical averaging. Our empirical results provide support for the new approach.

结合累积概率分布（CDFs）的预测，可以聚集可用信息以提高准确性。线性意见池是常用的，但它可能产生过于分散的分布预测。另一种导致较低分散的方法是对共同发展基金的分位数进行平均，这可被视为共同发展基金的水平平均，而对线性意见池中的概率进行平均则被视为垂直平均。实证结果表明，水平平均和垂直平均对CDF的不同部分都是较好的。例如，一种方法可能更适合尾部分位数，而另一种方法更适合中心分位数。为了解决这个问题，我们开发了一种在CDF上垂直和水平平均之间转换的方法。它与角度平均有关，这是最近提出的沿一定角度的线进行聚合的建议。我们的新方法沿着平滑过渡到CDF的斜率进行平均。该方法是分位数自适应的，因为直线的斜率在各个分位数上变化，或者等价地，在各个概率上变化。我们将这些线设置为从少量固定点发出，这些固定点是该方法的参数。把直线看成射线，我们称之为径向平均法。我们的理论结果表明，该方法具有通用性，可以生成比水平平均更清晰的CDF预测，而不像垂直平均那么清晰。我们的实证结果为新方法提供了支持。

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引用次数: 0

Machine scheduling instance generation by reverse engineering from instance space analysis 基于实例空间分析的逆向工程机器调度实例生成

IF 6 2区管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

European Journal of Operational Research

Pub Date : 2026-05-01 Epub Date: 2025-10-18 DOI: 10.1016/j.ejor.2025.10.029

Christian Gahm, Michael Wimmer, Axel Tuma

The availability of a sufficiently large number of meaningful instances for a scheduling problem is of utmost importance for the evaluation of solution methods for the problem. This study introduces a novel method for machine scheduling instance generation, termed Reverse Instance Generation (RIG), leveraging Instance Space Analysis. This method aims to create diverse, feasible, and realistic instances by reverse engineering from the instance space. Unlike existing approaches that rely on iterative search methods, RIG utilizes a constructive approach, combining dimensionality reduction techniques and controlled instance generation. The approach addresses the challenges of instance diversity and reasonableness, ensuring unbiased and reproducible outcomes. The effectiveness of RIG is demonstrated on three different machine scheduling problems: the single-machine weighted tardiness problem, the job shop scheduling problem, and a complex serial batch scheduling problem. The results highlight the method's ability to cover gaps in the instance space while maintaining practicality and efficiency, paving the way for improved benchmarking and algorithm development.

对于调度问题而言，是否有足够多的有意义的实例，对于评估该问题的求解方法至关重要。本研究引入了一种新的机器调度实例生成方法，称为反向实例生成（RIG），利用实例空间分析。该方法旨在通过对实例空间的逆向工程，创建多样化、可行和真实的实例。与现有的依赖于迭代搜索方法的方法不同，RIG采用了一种建设性的方法，结合了降维技术和受控实例生成。该方法解决了实例多样性和合理性的挑战，确保了结果的无偏性和可重复性。钻机的有效性证明了三个不同的机器调度问题：单机加权延迟问题，作业车间调度问题，和一个复杂的串行批调度问题。结果突出了该方法在保持实用性和效率的同时覆盖实例空间空白的能力，为改进基准测试和算法开发铺平了道路。

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引用次数: 0

The optimal repair policy for an unreliable production system with limited available spare parts 备件有限的不可靠生产系统的最佳维修策略

IF 6 2区管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

European Journal of Operational Research

Pub Date : 2026-05-01 Epub Date: 2025-09-21 DOI: 10.1016/j.ejor.2025.09.007

Ludwig Brieditis , Gudrun P. Kiesmüller , Filip Malmberg

In this study, a serial production system consisting of two machines and an intermediate finite buffer is considered. The machines have random processing times, and each machine contains one unit of a common critical component that is subject to random breakdown. Broken components must be replaced from an inventory of ready-for-use spare parts to restore machine functionality. This inventory is replenished according to a one-for-one replenishment policy with an externally given base stock level. Due to the limited availability of spare parts, the sequence in which the machines are to be repaired and whether they should be repaired immediately must be decided. The objective of our study is the maximization of the expected total discounted revenue per time unit over an infinite planning horizon.

We model the system as a semi-Markov decision process and characterize the optimal stationary repair policy. We show that the First-Break-First-Repair policy is not optimal and provide numerical evidence that the optimal repair decision depends on the number of units in the buffer and the number of available spare parts. We show that, in some system states, it is optimal to postpone repair of a machine and reserve spare parts for the other machine.

Since the optimal repair policy is state dependent and quite complex, we investigate different prioritization heuristics from the literature in a numerical study. Our experiments suggest that heuristics achieve excellent performance in practical settings.

本文研究了一个由两台机器和一个中间有限缓冲器组成的连续生产系统。这些机器的处理时间是随机的，每台机器包含一个常见关键部件的单元，该单元可能会随机故障。损坏的部件必须从现成的备件库存中更换，以恢复机器功能。这个库存是根据一个一对一的补充政策与外部给定的基础库存水平补充的。由于可用的备件有限，必须决定修理机器的顺序和是否应该立即修理。我们研究的目标是在无限规划范围内每时间单位的预期总折现收益最大化。

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引用次数: 0

Multi-cycle production network design under supply uncertainty 供应不确定性下的多周期生产网络设计

IF 6 2区管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

European Journal of Operational Research

Pub Date : 2026-05-01 Epub Date: 2025-09-23 DOI: 10.1016/j.ejor.2025.09.008

Nadia Jaoui , Walid Klibi , Nizar El Hachemi , Tarik Aouam , Michel Fender

This study addresses a novel production network design problem with an expanded scope inspired by a real-world business context. The problem involves strategic decisions for a long-term horizon regarding production sites’ location and capacity, suppliers’ selection, and transportation modes choice, given in-house vs external service providers’ options. To support these decisions, we integrate key tactical decisions for a large set of planning periods, involving flows between origin–destination pairs, production levels based on bill of materials, and inventory levels. Additionally, we consider uncertainty in raw material availability at suppliers, disruption in production capacities, and perturbation in transportation flows. First, we develop a multi-stage stochastic program that re-optimizes strategic decisions at each design period. Then, this program is reformulated into a multi-cycle two-stage stochastic model. Uncertainty is modeled through a finite set of scenarios generated using the Latin hypercube sampling technique, and the sample average approximation method is used to calibrate the sample size. Given the challenging solvability of the model, we proposed an advanced solution approach that builds on the recently introduced Partial Benders Decomposition (PBD) technique with new scenario creation strategies. Our experiments highlight the superiority of the proposed PBD’s variant in terms of solution quality and time reaching the best solution, compared to classical approaches. Furthermore, we demonstrate the benefits of enlarging the scope of the production network design problem by integrating all strategic decisions, which can yield gains of up to 36% compared to addressing them separately. Finally, we underscore the importance of stochastic modeling, contributing to cost reductions of over 3% compared to the deterministic counterpart.

本研究解决了一个新的生产网络设计问题，其扩展范围受到现实世界商业环境的启发。这个问题涉及到长期的战略决策，包括生产基地的位置和产能、供应商的选择和运输方式的选择，以及内部和外部服务提供商的选择。为了支持这些决策，我们集成了大量计划周期的关键战术决策，包括出发地-目的地对之间的流程、基于物料清单的生产水平和库存水平。此外，我们还考虑了供应商原材料供应的不确定性、生产能力的中断以及运输流的扰动。首先，我们开发了一个多阶段随机程序，在每个设计阶段重新优化战略决策。然后，将该方案重新表述为多周期两阶段随机模型。利用拉丁超立方采样技术生成的有限情景集对不确定性进行建模，并使用样本平均近似方法校准样本大小。鉴于该模型具有挑战性的可解性，我们提出了一种先进的解决方法，该方法基于最近引入的部分弯曲分解（PBD）技术和新的场景创建策略。与经典方法相比，我们的实验突出了所提出的PBD变体在解决方案质量和达到最佳解决方案的时间方面的优势。此外，我们展示了通过整合所有战略决策来扩大生产网络设计问题范围的好处，与单独解决这些问题相比，这可以产生高达36%的收益。最后，我们强调了随机建模的重要性，与确定性模型相比，它有助于降低超过3%的成本。

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引用次数: 0

Online platform demand information sharing with upstream suppliers under the imbalanced market power structure 在不平衡的市场权力结构下，在线平台与上游供应商的信息共享需求

IF 6 2区管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

European Journal of Operational Research

Pub Date : 2026-05-01 Epub Date: 2025-09-15 DOI: 10.1016/j.ejor.2025.09.009

Ruozhen Qiu , Xuge Li , Minghe Sun , Yue Sun , Zhi-Ping Fan

This work investigates online platform information sharing strategies in a supply chain consisting of an online platform and two, one leading (Supplier A) and the other following (Supplier B), suppliers with an imbalanced market power structure under the agency mode. The online platform has demand information, and the two suppliers engage in horizontal retail price competition. Four information sharing scenarios are examined, including no information sharing (S1), full information sharing (S2), information sharing with only Supplier A (S3), and information sharing with only Supplier B (S4). Game models, involving a signaling game for scenario S3, are formulated. The equilibrium solutions are further examined, the supply chain members’ preferences are analyzed among the four demand information sharing scenarios, and the equilibrium information sharing outcomes are obtained. The findings indicate that Supplier A prefers scenario S2, Supplier B prefers scenario S3, and the online platform prefers scenario S3 when the demand variability is high or low and prefers scenario S2 when the demand variability is moderate. The equilibrium information sharing outcome can be any of the scenarios depending on the demand variability and the supplier acceptance probabilities of the platform’s information sharing agreements. Extensions of the main model are explored. The equilibrium results of the main model are robust under asymmetric market potentials, intuitive criterion and divinity criterion. Under the resale mode, Supplier B prefers scenario S2 or S3, while other results remain unchanged. When the two suppliers are in a coopetition relationship, the theoretical outcomes are significantly different from those of the main model.

本文研究了在代理模式下，由一个在线平台和两个市场权力结构不平衡的供应商组成的供应链中，一个领先（供应商a）和一个从属（供应商B）的在线平台信息共享策略。线上平台有需求信息，两家供应商进行横向零售价格竞争。研究了四种信息共享场景，即不共享信息（S1）、完全共享信息（S2）、仅与供应商A共享信息（S3）、仅与供应商B共享信息（S4）。制定了博弈模型，包括场景S3的信令博弈。进一步检验了均衡解，分析了四种需求信息共享情景下供应链成员的偏好，得到了均衡信息共享结果。研究结果表明，供应商A偏好场景S2，供应商B偏好场景S3，在线平台在需求可变性高或低时偏好场景S3，在需求可变性中等时偏好场景S2。根据需求可变性和平台信息共享协议的供应商接受概率，均衡信息共享结果可以是任何一种情况。探讨了主要模型的扩展。在不对称市场潜力、直觉准则和神性准则下，主要模型的均衡结果具有鲁棒性。resale模式下，供应商B更倾向于场景S2或S3，其他结果不变。当两家供应商处于合作关系时，理论结果与主要模型有显著差异。

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引用次数: 0

Fifty years of stochastic simulation: Where we are and where we need to go 五十年的随机模拟：我们在哪里，我们需要去哪里

IF 6 2区管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

European Journal of Operational Research

Pub Date : 2026-05-01 Epub Date: 2025-07-09 DOI: 10.1016/j.ejor.2025.06.033

L. Jeff Hong , Barry L. Nelson

Stochastic computer simulation is the go-to tool for operational researchers designing and improving complex systems that must perform in the face of uncertainty. In this article, we reflect on key advances in simulation analysis methodology over the past 50 years and speculate on future research directions, employing three recent real applications of simulation to ground our discussion.

随机计算机模拟是操作研究人员设计和改进必须在不确定性面前运行的复杂系统的首选工具。在这篇文章中，我们回顾了过去50年来仿真分析方法的主要进展，并推测了未来的研究方向，采用了三个最近的仿真实际应用来为我们的讨论奠定基础。

引用次数: 0

Benders decompositions for order acceptance and scheduling in additive manufacturing 增材制造中用于订单接收和调度的弯管机分解

IF 6 2区管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

European Journal of Operational Research

Pub Date : 2026-05-01 Epub Date: 2025-10-04 DOI: 10.1016/j.ejor.2025.10.005

Jian Chen , Xudong Ye , Naiming Xie , Yao-Wen Sang , Malgorzata Sterna

We study an order acceptance and parallel machine scheduling problem appearing in additive manufacturing (AM) considering two-dimensional packing with part rotation. Three joint decisions, including order acceptance, build formation and schedule construction, are made to maximize the revenue of accepted orders minus a weighted makespan, thereby capturing the trade-off between profitability and production efficiency. First, two mixed integer programming models (MIP) are formulated to optimize the three mentioned decisions simultaneously. Then, due to the specific structure of the problem, we propose a general logic-based Benders decomposition (LBBD) approach and a nested logic-based Benders decomposition (NLBBD) approach with various Benders cuts and search strategies. Finally, we undertake a comprehensive computational study to validate the effectiveness of all the proposed approaches. The computational results show that NLBBD achieves 50 % more optimal solutions than MIP models implemented in Gurobi and 35 % more than LBBD for small-sized instances. For large-sized instances, NLBBD still achieves better solutions with smaller gaps compared to Gurobi and LBBD. Further, numerical experiments confirm the effectiveness of the designed additional cuts and search strategies applied in Benders decompositions.

研究了考虑零件旋转的二维包装的增材制造（AM）中出现的订单接受与并行机器调度问题。三个联合决策，包括订单接受、构建和进度构建，是为了使接受订单减去加权最大完工时间的收益最大化，从而捕获盈利能力和生产效率之间的权衡。首先，建立了两个混合整数规划模型（MIP）来同时优化上述三种决策。然后，由于问题的特殊结构，我们提出了一种基于一般逻辑的Benders分解（LBBD）方法和一种基于嵌套逻辑的Benders分解（NLBBD）方法，该方法具有各种Benders切割和搜索策略。最后，我们进行了全面的计算研究，以验证所有提出的方法的有效性。计算结果表明，对于小型实例，NLBBD比在robi实现的MIP模型获得的最优解多50%，比LBBD多35%。对于大型实例，NLBBD相比于Gurobi和LBBD仍然可以获得更好的解决方案，并且差距更小。此外，数值实验验证了所设计的附加切割和搜索策略在弯曲体分解中的有效性。

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引用次数: 0

Stochastic dynamic lot-sizing with supplier-driven substitution and service level constraints 供应商驱动替代和服务水平约束下的随机动态批量生产

IF 6 2区管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

European Journal of Operational Research

Pub Date : 2026-05-01 Epub Date: 2026-01-09 DOI: 10.1016/j.ejor.2026.01.007

Narges Sereshti , Merve Bodur , James R. Luedtke

We consider a multi-stage stochastic multi-product lot-sizing problem with service level constraints and supplier-driven product substitution. A firm has the option to meet demand from substitutable products at a cost. Considering the uncertainty in future demands, the firm wishes to make ordering decisions in every period such that the probability that all demands can be met in the next period meets or exceeds a minimum service level. We propose a rolling-horizon policy in which a two-stage joint chance-constrained stochastic program is solved to make decisions in each time period. We demonstrate how to effectively solve this formulation. In addition, we propose two policies based on deterministic approximations. On test problems with a downward substitution structure, we show that the proposed chance-constraint policy can achieve the service levels more reliably and at a lower cost. We also explore the value of product substitution in this model, demonstrating that the substitution option allows achieving service levels while reducing costs by 7% to 25% in our experiments, and that the majority of the benefit can be obtained with limited levels of substitution allowed.

研究了具有服务水平约束和供应商驱动产品替代的多阶段随机多产品批量问题。企业可以选择以一定的成本来满足可替代产品的需求。考虑到未来需求的不确定性，企业希望在每个时期做出订货决策，使所有需求在下一个时期得到满足的概率达到或超过最低服务水平。我们提出了一种滚动地平线策略，该策略求解了一个两阶段联合机会约束随机规划，在每个时间段内进行决策。我们将演示如何有效地求解这个公式。此外，我们提出了两种基于确定性近似的策略。在具有向下替代结构的测试问题上，我们证明了所提出的机会约束策略能够以较低的成本更可靠地达到服务水平。我们还在该模型中探讨了产品替代的价值，证明替代选项允许在达到服务水平的同时降低实验中7%至25%的成本，并且在允许的有限替代水平下可以获得大部分收益。

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引用次数: 0