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

Eco-efficiency or eco-differentiation: Strategic prioritization of environmental investments 生态效率或生态分化：环境投资的战略优先顺序

IF 6.4 2区管理学

European Journal of Operational Research Pub Date : 2025-07-05 DOI: 10.1016/j.ejor.2025.06.021

Arda Yenipazarli

{"title":"Eco-efficiency or eco-differentiation: Strategic prioritization of environmental investments","authors":"Arda Yenipazarli","doi":"10.1016/j.ejor.2025.06.021","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.06.021","url":null,"abstract":"Effective prioritization of environmental investments is critical for firms seeking to achieve sustainable competitive advantage and maximize economic returns. Many environmental initiatives fail due to the absence of a structured “choice” framework, which leads firms to adopt a scattered approach of doing “a bit of everything”—a strategy that squanders limited resources and undermines future innovation efforts. To address this lack of structured guidance, we develop a game-theoretic model that formalizes the strategic prioritization problem firms face when allocating resources between two archetypal environmental innovation strategies, distilled from recurring patterns in corporate practice, industry reports, and academic literature: <ce:italic>eco-differentiation</ce:italic> (a demand-enhancing, product-oriented investment with high failure risk, delayed payoff, and substantial capital outlay) and <ce:italic>eco-efficiency</ce:italic> (a cost-reducing, process-oriented investment with minimal risk, short lead time, and lower capital outlay). Our model incorporates strategic rivalry, firm-specific innovation capabilities, innovation failure risks, product development lead times, and consumer heterogeneity in both brand and environmental preferences—alongside a novel interaction between these two preference dimensions—as well as an endogenous transition in market structure triggered by the successful introduction of eco-differentiated products. Our equilibrium analysis establishes explicit innovative capability thresholds that delineate equilibrium regions and characterize firms’ optimal environmental investment choices. Our theoretical findings provide actionable insights to help firms—particularly those with limited resources—tailor their environmental investment choices to industry- and market-specific constraints, enabling them to translate sustainability efforts into sources of sustained profitability and competitive advantage.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"93 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144613320","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 data-driven approach for strategic inventory placement in multi-echelon supply networks 多层次供应网络中战略性库存配置的数据驱动方法

IF 6.4 2区管理学

European Journal of Operational Research Pub Date : 2025-07-04 DOI: 10.1016/j.ejor.2025.06.022

Josef Svoboda, Stefan Minner

{"title":"A data-driven approach for strategic inventory placement in multi-echelon supply networks","authors":"Josef Svoboda, Stefan Minner","doi":"10.1016/j.ejor.2025.06.022","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.06.022","url":null,"abstract":"This paper provides a data-driven solution for optimizing inventory buffers in large-scale supply networks. We study the placement and sizing of strategic inventories in multi-echelon supply chains where the decision maker faces uncertain demand with an unknown distribution influenced by explanatory variables. State-of-the-art multi-echelon inventory optimization models, such as the well-known guaranteed-service model (GSM), are non-linear and typically informed by distributional and parametric assumptions. They often rely on dynamic programming and are difficult to solve for large networks. We adapt the GSM to introduce a nonparametric, feature-driven approach to supply chain safety stock optimization that is based on mixed-integer linear programming (MILP). The MILP formulation sets cost-optimal base stocks, which are learned as linear functions of feature data under consideration of service level requirements. This integrated estimation and optimization approach is solved with commercial mathematical programming solvers and is enhanced by a Benders decomposition method for large networks. We extend the literature on data-driven inventory control by a multi-period and multi-echelon approach for safety stock planning in general, acyclic networks. On the real-world networks from Willems (2008), we find that incorporating feature information when setting safety stocks in large supply chains, on average, reduces operational costs out-of-sample. This value of feature information that the proposed model offers to decision-makers increases in demand volatility and is dependent on certain network characteristics.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"36 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144613322","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

Data-driven joint optimization of maintenance and spare parts provisioning: A distributionally robust approach 数据驱动的维护和备件供应联合优化：一种分布式鲁棒方法

IF 6.4 2区管理学

European Journal of Operational Research Pub Date : 2025-07-03 DOI: 10.1016/j.ejor.2025.06.025

Heraldo Rozas, Weijun Xie, Nagi Gebraeel, Stephen Robinson

{"title":"Data-driven joint optimization of maintenance and spare parts provisioning: A distributionally robust approach","authors":"Heraldo Rozas, Weijun Xie, Nagi Gebraeel, Stephen Robinson","doi":"10.1016/j.ejor.2025.06.025","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.06.025","url":null,"abstract":"This paper investigates the joint optimization of condition-based maintenance and spare provisioning, incorporating insights obtained from sensor data. Prognostic models estimate components’ remaining lifetime distributions (RLDs), which are integrated into an optimization model to coordinate maintenance and spare provisioning. The existing literature addressing this problem assumes that prognostic models provide accurate estimates of RLDs, thereby allowing a direct adoption of Stochastic Programming or Markov Decision Process methodologies. Nevertheless, this assumption often does not hold in practice since the estimated distributions can be inaccurate due to noisy sensors or scarcity of training data. To tackle this issue, we develop a Distributionally Robust Chance Constrained (DRCC) formulation considering general discrepancy-based ambiguity sets that capture potential distribution perturbations of the estimated RLDs. The proposed formulation admits a Mixed-Integer Linear Programming (MILP) reformulation, where explicit formulas are provided to simplify the general discrepancy-based ambiguity sets. Finally, for the numerical illustration, we test a type-<mml:math altimg=\"si1.svg\" display=\"inline\"><mml:mi>∞</mml:mi></mml:math> Wasserstein ambiguity set and derive closed-form expressions for the parameters of the MILP reformulation. The efficacy of our methodology is showcased in a wind turbine case study, where the proposed DRCC formulation outperforms other benchmarks based on stochastic programming and robust optimization.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"109 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144613336","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

Fifty years of inventory research from a forecasting perspective 从预测的角度进行了五十年的库存研究

IF 6.4 2区管理学

European Journal of Operational Research Pub Date : 2025-07-02 DOI: 10.1016/j.ejor.2025.07.003

M. Zied Babai, Aris A. Syntetos, Ruud H. Teunter

引用次数: 0

A bilevel multistage stochastic self-scheduling model with indivisibilities for trading in the continuous intraday electricity market 一个具有不可分性的两级多阶段随机自调度模型

IF 6.4 2区管理学

European Journal of Operational Research Pub Date : 2025-06-30 DOI: 10.1016/j.ejor.2025.06.002

Priyanka Shinde, Ignacio Aravena

{"title":"A bilevel multistage stochastic self-scheduling model with indivisibilities for trading in the continuous intraday electricity market","authors":"Priyanka Shinde, Ignacio Aravena","doi":"10.1016/j.ejor.2025.06.002","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.06.002","url":null,"abstract":"In this paper, we study the profit maximization problem of a virtual power plant trading in the continuous intraday electricity market. Our virtual power plant model is compatible with renewable, and thermal assets, covering a range of virtual power plants currently participating in energy markets. We model the trading problem as a bilevel multistage stochastic program. The upper level of the problem accounts for the profit maximization of the virtual power plant with explicit modeling of the technical constraints of the operational status of the thermal power plant including minimum start-up and shut-down times, ramp-up and ramp-down rates, and minimum generation level. The upper level also decides which continuous and indivisible (fill-or-kill) orders are submitted to the market. The lower-level problem accounts for the clearing of the continuous intraday market, i.e., matching of buy and sell orders. Because of the presence of fill-or-kill orders, the lower-level problem is mixed-integer, which prevents its direct conversion to a single-level problem using duality. In order to solve this challenging problem, we develop a convex-hull extended formulation for the lower-level problem, apply duality theory to obtain a single-level stochastic equivalent formulation, and employ McCormick envelopes to turn the problem into a multistage stochastic mixed-integer linear problem, which we solve using the stochastic dual dynamic integer programming algorithm. We conduct numerical experiments and analyze the optimal trading behavior of a virtual power plant trading in an ideal continuous market without arbitrage.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"10 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144566088","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 split-embedded metaheuristic for the heterogenous inventory routing problem with batch size 具有批量大小的异构库存路径问题的分段嵌入元启发式算法

IF 6.4 2区管理学

European Journal of Operational Research Pub Date : 2025-06-27 DOI: 10.1016/j.ejor.2025.05.044

Diego Perdigão Martino, Philippe Lacomme, Katyanne Farias

{"title":"A split-embedded metaheuristic for the heterogenous inventory routing problem with batch size","authors":"Diego Perdigão Martino, Philippe Lacomme, Katyanne Farias","doi":"10.1016/j.ejor.2025.05.044","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.05.044","url":null,"abstract":"Handling transportation and inventory management simultaneously is a challenging problem. The most famous optimization problem in this domain, known as the Inventory Routing Problem (IRP), aims to determine the routes and quantities to be delivered by a set of vehicles to meet customer demands at a minimum total inventory and transportation cost. The vast majority of works carried out so far on the IRP consider a homogeneous fleet of vehicles. This paper addresses, instead, a new IRP variant that considers intrinsic characteristics of real supply chains, such as a period-dependent heterogeneous fleet of vehicles and batch sizes for the delivered quantites. We model the problem with a Mixed Integer Linear Programming (MILP) formulation and propose a Split-Embedded Metaheuristic with a Post-Optimization phase (SEMPO) to solve it. Extensive computational experiments are conducted on a set of 80 new benchmark instances with up to 183 customers and a challenging time horizon of up 7 to 28 time periods to evaluate the performance of our approaches. The proposed SEMPO algorithm provides high-quality solutions and faster convergence compared to the MILP formulation.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"10 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144515809","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

Probabilistic Forecast Aggregation with Statistical Depth 具有统计深度的概率预测聚合

IF 6.4 2区管理学

European Journal of Operational Research Pub Date : 2025-06-27 DOI: 10.1016/j.ejor.2025.06.028

James W. Taylor

{"title":"Probabilistic Forecast Aggregation with Statistical Depth","authors":"James W. Taylor","doi":"10.1016/j.ejor.2025.06.028","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.06.028","url":null,"abstract":"This paper considers aggregation methods for interval forecasts and forecasts of cumulative distribution functions (CDFs) when there are many forecasters, and past forecast accuracy may not be known. For aggregation, the median and trimmed means have been proposed as simple and robust alternatives to the mean, with some trimmed mean approaches enabling recalibration to widen or narrow the resulting interval or CDF forecast. For interval forecast aggregation, the median and trimming are applied to each bound separately. To try to use the available information better, we treat the bounds as a bivariate point with statistical depth used to order the points in terms of centrality. The deepest point can be viewed as the median interval forecast, and the depth of each point can be used as the basis for trimming. For CDF forecasts, the literature presents aggregation methods for which the median or trimmed mean are obtained for each point on the domain of the distribution. However, if one part of a CDF forecast is outlying, the appeal of using the rest of the CDF forecast is perhaps reduced. We use functional depth to provide a measure of centrality for each CDF forecast, and hence identify the deepest function, which can be viewed as the median forecast. We also use functional depth as the basis for trimming, and consider weighted depth to control the width of the resulting aggregated interval or CDF forecast. We provide empirical illustration using data from surveys of professional macroeconomic forecasters, and an application to growth-at-risk.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"33 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144515806","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 reverse Stackelberg model for demand response in local energy markets 本地能源市场需求响应的反向Stackelberg模型

IF 6.4 2区管理学

European Journal of Operational Research Pub Date : 2025-06-27 DOI: 10.1016/j.ejor.2025.06.017

Juan Sepúlveda, Luce Brotcorne, Hélène Le Cadre

{"title":"A reverse Stackelberg model for demand response in local energy markets","authors":"Juan Sepúlveda, Luce Brotcorne, Hélène Le Cadre","doi":"10.1016/j.ejor.2025.06.017","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.06.017","url":null,"abstract":"In an era where renewable energy resources are increasingly integrated into our power systems, and consumer-centric approaches gain traction, local energy markets emerge as a pivotal mechanism for empowering prosumers. This paper presents a novel bilevel optimization model that uniquely blends the dynamics of peer–to–peer energy markets with the physical realities of power distribution networks. The innovation steems from introducing a tariff design approach based on affine functions to shape prosumer behavior towards operationally efficient and secure energy exchanges. This is critical as previous market designs often overlooked the physical constraints of power flows, leading to potential risks in voltage regulation and economic efficiency. The lower level of the model encapsulates the interactions among prosumers in a generalized Nash equilibrium problem (GNEP), modeling active and reactive power injections of prosumers. The upper level, representing the role of the distribution system operator, strategically computes tariffs to steer the market to an operationally efficient equilibrium. The paper relies on the classical Nikaido–Isoda (NI) reformulation to characterize the GNEP, a key aspect in leveraging a proof of strong stability of the lower–level solution. Computational experiments on various IEEE test feeder instances reveal the model’s capacity to efficiently align prosumer behavior with operational objectives, utilizing only the tariff information, thereby simplifying the decision-making process in complex distribution systems.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"7 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144515807","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

Using diet optimization and machine learning for the design of healthy and acceptable menu plans 使用饮食优化和机器学习来设计健康和可接受的菜单计划

IF 6.4 2区管理学

European Journal of Operational Research Pub Date : 2025-06-27 DOI: 10.1016/j.ejor.2025.06.015

Dominique van Wonderen, Johanna C. Gerdessen, Alida Melse-Boonstra, Marleen C. Onwezen

{"title":"Using diet optimization and machine learning for the design of healthy and acceptable menu plans","authors":"Dominique van Wonderen, Johanna C. Gerdessen, Alida Melse-Boonstra, Marleen C. Onwezen","doi":"10.1016/j.ejor.2025.06.015","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.06.015","url":null,"abstract":"The success of dietary plans relies on understanding and modelling consumer acceptance, yet quantifying this poses a challenge due to the complexity of individual preferences. Recent research is focused on deriving acceptability constraints directly from data, as demonstrated by its application in designing food baskets with a limited number of commodities. In this study, we applied diet optimization with machine learning to the more complex task of menu planning. This involved considering hundreds of potential food alternatives and assessing their compatibility within a meal using a recipe completion algorithm. Compared to the traditional diet modelling approach of food group filtering, the recipe completion model delivered diets with either higher nutritional adequacy or greater substitute acceptability, depending on the number of food groups used in the traditional method. While more research is needed to further improve the acceptability of substitutions, combining diet optimization with recipe completion presents a promising approach to enhance the nutritional adequacy of individual diets while maintaining the acceptability of food combinations within meals.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"49 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144515808","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

Beyond fifty years of vehicle routing: Insights into the history and the future 超越五十年的车辆路线：洞察历史和未来

IF 6.4 2区管理学

European Journal of Operational Research Pub Date : 2025-06-26 DOI: 10.1016/j.ejor.2025.06.014

C. Archetti, L.C. Coelho, M.G. Speranza, P. Vansteenwegen

引用次数: 0