European Journal of Operational Research最新文献_第4页

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 6.4 2区管理学

European Journal of Operational Research Pub Date : 2025-09-23 DOI: 10.1016/j.ejor.2025.09.008

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

{"title":"Multi-cycle production network design under supply uncertainty","authors":"Nadia Jaoui, Walid Klibi, Nizar El Hachemi, Tarik Aouam, Michel Fender","doi":"10.1016/j.ejor.2025.09.008","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.09.008","url":null,"abstract":"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.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"98 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145228926","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}

引用次数: 0

Markov decision processes: Monotonicity of optimal policy in exponential and quasi-hyperbolic discounting parameters 马尔可夫决策过程：指数型和拟双曲型贴现参数下最优策略的单调性

IF 6 2区管理学

European Journal of Operational Research Pub Date : 2025-09-23 DOI: 10.1016/j.ejor.2025.09.013

Hakan Kılıç , Pelin Gülşah Canbolat , Evrim Didem Güneş

{"title":"Markov decision processes: Monotonicity of optimal policy in exponential and quasi-hyperbolic discounting parameters","authors":"Hakan Kılıç , Pelin Gülşah Canbolat , Evrim Didem Güneş","doi":"10.1016/j.ejor.2025.09.013","DOIUrl":"10.1016/j.ejor.2025.09.013","url":null,"abstract":"<div><div>Intertemporal preferences of decision makers, i.e., the way they discount delayed utilities, impact their decisions. Empirical evidence suggests that individuals commonly have hyperbolic discounting preferences. This can result in time-inconsistent behavior, e.g., procrastination, which may be a barrier to adopting preventive behavior such as machine maintenance and patient adherence to treatment. In this paper, we theoretically compare the actions of individuals based on their discounting characteristics. We consider the Hyperbolic Discounting (HD) model, which is more representative of individual behavior than Exponential Discounting (ED). We formulate a discrete-time finite-horizon Markov decision process with Quasi-Hyperbolic Discounting (QHD), an analytically tractable function representing HD and present sufficient conditions that ensure the monotonicity of the optimal policy in the discounting parameters. We consider submodular maximization or supermodular maximization problems. Our paper is the first to investigate the monotonicity of the optimal policy in QHD parameters for these problems. Moreover, we compare the optimal actions under ED and QHD. We apply our results to the settings of machine maintenance, individual health behavior and inventory control. We provide numerical examples that show there might not be monotonicity if our sufficient conditions are not met. Also, we explore the discrepancy between the expected total exponentially-discounted rewards of the actions obtained from QHD and of the actions that are optimal under ED, and observe that this discrepancy is affected mainly by the present bias.</div></div>","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"328 3","pages":"Pages 877-893"},"PeriodicalIF":6.0,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145181247","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}

引用次数: 0

Reinforcement learning algorithm for reusable resource allocation with unknown rental time distribution 租赁时间分布未知的可重用资源分配的强化学习算法

IF 6.4 2区管理学

European Journal of Operational Research Pub Date : 2025-09-22 DOI: 10.1016/j.ejor.2025.09.012

Ziwei Wang, Jie Song, Yixuan Liu, Jingtong Zhao

{"title":"Reinforcement learning algorithm for reusable resource allocation with unknown rental time distribution","authors":"Ziwei Wang, Jie Song, Yixuan Liu, Jingtong Zhao","doi":"10.1016/j.ejor.2025.09.012","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.09.012","url":null,"abstract":"We explore a scenario where a platform must decide on the price and type of reusable resources for sequentially arriving customers. The product is rented for a random period, during which the platform also extracts rewards based on a prearranged agreement. The expected reward varies during the usage time, and the platform aims to maximize revenue over a finite horizon. Two primary challenges are encountered: the stochastic usage time introduces uncertainty, affecting product availability, and the platform lacks initial knowledge about reward and usage time distributions. In contrast to conventional online learning, where usage time distributions are parametric, our problem allows for unknown distribution types. To overcome these challenges, we formulate the problem as a Markov decision process and model the usage time distribution using a hazard rate. We first introduce a greedy policy in the full-information setting with a provable 1/2-approximation ratio. We then develop a reinforcement learning algorithm to implement this policy when the parameters are unknown, allowing for non-parametric distributions and time-varying rewards. We further prove that the algorithm achieves sublinear regret against the greedy policy. Numerical experiments on synthetic data as well as a real dataset from TikTok demonstrate the effectiveness of our method.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"326 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145181242","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}

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 6.4 2区管理学

European Journal of Operational Research Pub Date : 2025-09-21 DOI: 10.1016/j.ejor.2025.09.007

Ludwig Brieditis, Gudrun P. Kiesmüller, Filip Malmberg

引用次数: 0

A stochastic location-inventory problem in multi-period closed-loop leased pallet pooling systems with palletized transport 具有托盘运输的多周期闭环租赁托盘池系统的随机定位-库存问题

IF 6.4 2区管理学

European Journal of Operational Research Pub Date : 2025-09-20 DOI: 10.1016/j.ejor.2025.09.029

Xiangling Hu, Ying Dai, Fei Yang, Zujun Ma

{"title":"A stochastic location-inventory problem in multi-period closed-loop leased pallet pooling systems with palletized transport","authors":"Xiangling Hu, Ying Dai, Fei Yang, Zujun Ma","doi":"10.1016/j.ejor.2025.09.029","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.09.029","url":null,"abstract":"Leased pallet pooling is widely adopted by companies using palletized transport to avoid supply chain complexity. This study investigates the integrated location-inventory problem with stochastic demand and returns in multi-period closed-loop leased pallet pooling systems with palletized transport (LPPS-PT), considering hierarchical operation centres (OCs), cyclic inventory in both forward and reverse flows, cross-regional and cross-enterprise characteristics of palletized transport, and initializing inventory configuration. The incorporated factors particularly complicate the distribution and return of leased pallets, leading to highly interdependent and complex location and inventory decisions. The problem is formulated as a two-stage stochastic programming model and solved by a tailored sample average approximation framework embedded with a progressive hedging algorithm with scenario bundles. Numerical experiments are performed on instances generated from real-world data to prove the efficiency of the proposed method. We observe that the LPPS-PT with hierarchical OCs enhances cost-effectiveness and enjoys economies of scale, the indicators of the palletized transport network and the quality of returned pallets significantly affect LPPS-PT design, and the type of stochastic demand has little effect on strategic decisions but considerably affects tactical decisions. Some managerial insights are drawn from the results.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"18 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145181244","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}

引用次数: 0

A unified and computationally efficient framework for procurement portfolio optimization with option contracts 一个统一的、计算效率高的期权合同采购组合优化框架

IF 6.4 2区管理学

European Journal of Operational Research Pub Date : 2025-09-20 DOI: 10.1016/j.ejor.2025.09.003

Xinyu Wang, Jiafu Tang, Bo Chen, Bin Hou

{"title":"A unified and computationally efficient framework for procurement portfolio optimization with option contracts","authors":"Xinyu Wang, Jiafu Tang, Bo Chen, Bin Hou","doi":"10.1016/j.ejor.2025.09.003","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.09.003","url":null,"abstract":"Efficient procurement decisions are crucial for maintaining stable material flows in competitive supply chains. This paper introduces a unified and computationally efficient framework for the procurement portfolio problem with option contracts (PPP-OC) in a two-echelon supply chain, consisting of multiple suppliers and one buyer. The buyer, facing uncertain demand, must reserve capacity from suppliers who offer a two-part fee structure: option price and strike price. We equivalently transform the PPP-OC into a transportation problem (TP) that can be solved efficiently. We propose three dominance rules among option contracts to filter out invalid options, simplifying the problem. Additionally, we present a binary-search-based (BSB) algorithm, offering significantly lower computational complexity than existing methods. We also address five PPP-OC variants, namely, procurement settings with fixed costs and a reserving quantity window, stockout allowances, spot market integration, multi-channel procurement with supply risks, and block reservations. These variants are solved efficiently using our TP-based framework, demonstrating the flexibility and robustness of our framework across various procurement settings. An extensive numerical study evaluates the efficiency of our proposed solution methods in various procurement scenarios, verifies the dominance rules and identifies active options, and examines the sensitivity of the optimal solution to varying stockout cost, demand variability, and levels of supply risk.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"77 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145228800","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}

引用次数: 0

Continuous-time optimal investment with portfolio constraints: A reinforcement learning approach 具有投资组合约束的连续时间最优投资：一种强化学习方法

IF 6 2区管理学

European Journal of Operational Research Pub Date : 2025-09-17 DOI: 10.1016/j.ejor.2025.08.032

Huy Chau , Duy Nguyen , Thai Nguyen

{"title":"Continuous-time optimal investment with portfolio constraints: A reinforcement learning approach","authors":"Huy Chau , Duy Nguyen , Thai Nguyen","doi":"10.1016/j.ejor.2025.08.032","DOIUrl":"10.1016/j.ejor.2025.08.032","url":null,"abstract":"<div><div>In a reinforcement learning (RL) framework, we study the exploratory version of the continuous time expected utility (EU) maximization problem with a portfolio constraint that includes widely-used financial regulations such as short-selling constraints and borrowing prohibition. The optimal feedback policy of the exploratory unconstrained classical EU problem is shown to be Gaussian. In the case where the portfolio weight is constrained to a given interval, the corresponding constrained optimal exploratory policy follows a truncated Gaussian distribution. We verify that the closed form optimal solution obtained for logarithmic utility and quadratic utility for both unconstrained and constrained situations converge to the non-exploratory expected utility counterpart when the exploration weight goes to zero. Finally, we establish a policy improvement theorem and devise an implementable reinforcement learning algorithm by casting the optimal problem in a martingale framework. Our numerical examples show that exploration leads to an optimal wealth process that is more dispersedly distributed with heavier tail compared to that of the case without exploration. This effect becomes less significant as the exploration parameter is smaller. Moreover, the numerical implementation also confirms the intuitive understanding that a broader domain of investment opportunities necessitates a higher exploration cost. Notably, when subjected to both short-selling and money borrowing constraints, the exploration cost becomes negligible compared to the unconstrained case.</div></div>","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"328 3","pages":"Pages 1068-1092"},"PeriodicalIF":6.0,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145094135","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}

引用次数: 0

A flow shop scheduling problem with machine-dependent speeds: An ensemble approach with worst-case analysis 具有机器依赖速度的流水车间调度问题：最坏情况分析的集成方法

IF 6.4 2区管理学

European Journal of Operational Research Pub Date : 2025-09-16 DOI: 10.1016/j.ejor.2025.09.018

Insoo Park, Kangbok Lee, Michael Pinedo

引用次数: 0

On the transition from make-to-stock to make-to-order 关于从制造到库存到制造到订单的转变

IF 6.4 2区管理学

European Journal of Operational Research Pub Date : 2025-09-16 DOI: 10.1016/j.ejor.2025.08.053

Yogendra Singh, Stephen M. Disney

引用次数: 0

Graph model for multiple composite decision makers with large-scale groups: Probability-hesitant fuzzy preference modeling and application 大规模群体多复合决策者的图模型：概率犹豫模糊偏好建模及应用

IF 6.4 2区管理学

European Journal of Operational Research Pub Date : 2025-09-16 DOI: 10.1016/j.ejor.2025.09.014

Nannan Wu, Yejun Xu, Zaiwu Gong, D. Marc Kilgour, Liping Fang

{"title":"Graph model for multiple composite decision makers with large-scale groups: Probability-hesitant fuzzy preference modeling and application","authors":"Nannan Wu, Yejun Xu, Zaiwu Gong, D. Marc Kilgour, Liping Fang","doi":"10.1016/j.ejor.2025.09.014","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.09.014","url":null,"abstract":"Whenever humans interact with others, conflict inevitably arises. Sometimes, multiple composite decision makers (CDMs) are involved, some of which may be large-scale groups. When making a decision or strategy selection, a CDM needs to consider the interests of the group and the wishes of individual decision makers (IDMs). For example, a CDM may judge a move to be an improvement only if a certain fraction of IDMs consider it so – in other words, only when the IDMs reach a certain degree of consensus. This paper proposes an index of group consensus on more preferred (IGCMP) and an index of group consensus on less preferred (IGCLP), and uses them to determine whether a CDM more or less prefers the current state to another and reflect the heterogeneous characteristics of CDMs, including conservative, aggressive, and eclectic. Accordingly, the conflict for multiple CDMs with large-scale groups is investigated in this paper from the perspective of group consensus within the framework of the Graph Model for Conflict Resolution (GMCR). At first, CDMs’ preferences are represented by probability-hesitant fuzzy preference relations, which can reflect the heterogeneity of IDMs and preference uncertainty of CDMs. Then, the new forms of the unilateral improvement list for CDMs and coalitions are developed based on IGCMP and IGCLP. Subsequently, five extended stability definitions and their relationships are studied. Finally, to demonstrate the effectiveness of the new method, it is applied to model a water pollution conflict in the Yangtze River Delta, China.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"60 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145094100","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}

引用次数: 0