{"title":"An adaptive hybrid algorithm with system participants classification for efficient convex hull pricing in electricity markets","authors":"Shifei Chen, Linfeng Yang, Xinhan Lin, Cuo Zhang","doi":"10.1016/j.ejor.2025.09.036","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.09.036","url":null,"abstract":"Due to the non-convexities in electricity market, system operators may need to provide side payments to incentivize participants to follow the production plans. Convex hull prices, derived from the Lagrange dual of the unit commitment problem (typically modeled as a mixed-integer programming problem), can minimize these side payments. We present an adaptive hybrid algorithm designed to efficiently compute convex hull prices by approaching the convex primal formulation of this Lagrange dual problem asymptotically. The algorithm classifies system participants into four groups based on the complexity of their convex hull descriptions and applies tailored convex hull formulations or column/row generation techniques to each group. By seamlessly integrating advanced models and algorithms within a unified primal framework, our approach enhances both computational efficiency and accuracy. We evaluated the algorithm on 40 instances and compared its performance against other methods, including column generation, row generation, and the Level Method. Results demonstrate that our adaptive hybrid algorithm reduces computation time by at least 90 % compared to the traditional Level Method. These findings confirm the algorithm’s computational feasibility for large-scale market clearing problems.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"46 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145228799","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}
Hamed Ghoddusi, Alexander Rodivilov, Baran Siyahhan
{"title":"Dynamic pricing when consumers have real options","authors":"Hamed Ghoddusi, Alexander Rodivilov, Baran Siyahhan","doi":"10.1016/j.ejor.2025.09.034","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.09.034","url":null,"abstract":"We study optimal dynamic pricing under uncertainty in a platform ecosystem subject to technological uncertainty. We highlight that users joining the platform before the full development of the complementary goods and services obtain real options to benefit from future improvements in platform quality and network effects. The platform owner influences the network effects and equilibrium outcomes through its dynamic price policy that trades off building an earlier consumer base versus extracting rents from early adopters. A price-skimming policy is optimal when the cost of developing a complementary good is small. Interestingly, price-skimming becomes optimal when the development cost is high, as long as the value of the improved platform is either small or relatively high. For intermediate values, however, the platform adopts a price-penetration policy. Our paper provides new insights for building markets subject to the network effect under uncertainty.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"5 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145228795","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}
Christian Fieberg, Carlos Osorio, Thorsten Poddig, Armin Varmaz
{"title":"Enhancing index-tracking performance: Leveraging characteristic-based factor models for reduced estimation errors","authors":"Christian Fieberg, Carlos Osorio, Thorsten Poddig, Armin Varmaz","doi":"10.1016/j.ejor.2025.08.043","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.08.043","url":null,"abstract":"This paper addresses the challenge of minimizing tracking error in passive portfolio management by reducing estimation errors commonly encountered in traditional optimization methods. We introduce an innovative cardinality-constrained mixed-integer optimization framework that incorporates characteristic-based factor models to enhance index-tracking performance. By leveraging these models, our approach aims to minimize errors stemming from estimation uncertainty. In an empirical analysis, we benchmark the tracking errors of our approach against traditional methods, examining both linear and quadratic programs. We further evaluate robustness across various stock market indices, time periods, solvers, and transaction costs. The results indicate that our method consistently reduces estimation errors, achieving superior tracking performance relative to conventional techniques. These findings provide crucial guidance for efficiently optimizing index-tracking portfolios while accommodating practical constraints.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"32 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145228798","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":"Efficient and accurate simulation of the stochastic-alpha-beta-rho model","authors":"Jaehyuk Choi, Lilian Hu, Yue Kuen Kwok","doi":"10.1016/j.ejor.2025.09.027","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.09.027","url":null,"abstract":"We propose an efficient, accurate and reliable simulation scheme for the stochastic-alpha-beta-rho (SABR) model. The two challenges of the SABR simulation lie in sampling (i) integrated variance conditional on terminal volatility and (ii) terminal forward price conditional on terminal volatility and integrated variance. For the first sampling procedure, we sample the conditional integrated variance using the moment-matched shifted lognormal approximation. For the second sampling procedure, we approximate the conditional terminal forward price as a constant-elasticity-of-variance (CEV) distribution. Our CEV approximation preserves the martingale condition and precludes arbitrage, which is a key advantage over Islah’s approximation used in most SABR simulation schemes in the literature. We then adopt the exact sampling method of the CEV distribution based on the shifted-Poisson mixture Gamma random variable. Our enhanced procedures avoid the tedious Laplace inversion algorithm for sampling integrated variance and non-efficient inverse transform sampling of the forward price in some of the earlier simulation schemes. Numerical results demonstrate our simulation scheme to be highly efficient, accurate, and reliable.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"158 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145228834","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":"Centroid cross-efficiency approach for clustering","authors":"Qingxian An, Jing Zhao, Ya Chen, Haoxun Chen","doi":"10.1016/j.ejor.2025.09.038","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.09.038","url":null,"abstract":"Recognizing the critical importance of explainable clustering results for decision-making and the influence of sample importance on the clustering result, this study proposes a clustering method based on the centroid data envelopment analysis (DEA) cross-efficiency approach. Specifically, this study first introduces the centroid DEA cross-efficiency approach. The approach is constructed based on the unique set of centroid weights of the convex polytope formed by all optimal weight vectors for each DMU. Then, a gravity model is constructed based on the centroid DEA cross-efficiency approach. The gravity model simultaneously accounts for the sample importance and the distance between samples. Based on the gravity between samples, this study develops the gravity clustering method. This clustering method enhances interpretability and provides decision support by identifying the importance degree of the features for samples across different clusters through centroid weights. To validate the effectiveness, an empirical example is conducted, and the result shows that the proposed clustering method outperforms existing DEA-based clustering approaches. Furthermore, a clustering study is conducted on the healthcare levels of various provinces in China, and policy recommendations are provided for the medical development of provinces within different clusters.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"63 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145228796","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":"Enhancing operational decision-making in fault diagnosis for high-dimensional data streams with auxiliary information","authors":"Zhihan Zhang, Wendong Li, Min Xie, Dongdong Xiang","doi":"10.1016/j.ejor.2025.09.022","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.09.022","url":null,"abstract":"Modern engineering systems, from advanced manufacturing processes to sophisticated electronic devices, generate high-dimensional data streams (HDS) that demand efficient operational strategies for quality management. While real-time anomaly detection is crucial, the importance of accurate post-signal fault diagnosis for root cause analysis has grown substantially. Current diagnostic methods often focus on isolated sequences of HDS, missing opportunities to leverage auxiliary information that can enhance decision-making. This paper introduces a novel framework to improve large-scale fault diagnosis in HDS environments, integrating auxiliary sequences within a multi-sequence multiple testing framework. Utilizing a Cartesian hidden Markov model, we develop a generalized local index of significance (GLIS) to assess the abnormality likelihood across data streams. Based on the GLIS, our proposed data-driven diagnostic procedure effectively harnesses auxiliary information, aiming to optimize operational decisions by minimizing the expected number of false positives in the primary sequence while maintaining control over the missed discovery rate. The asymptotic validity and optimality of this approach ensure its robustness in practical settings. We validate the efficacy of our method through comprehensive simulations and a real-world case study, demonstrating its potential to support more accurate and informed operational decisions.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"14 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145228832","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":"Solving the multi-block order batching problem with branch-price-and-cut","authors":"Julia Wahlen","doi":"10.1016/j.ejor.2025.08.055","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.08.055","url":null,"abstract":"In the realm of warehouse optimization, the order batching problem (OBP) involves partitioning customer orders into capacity-constrained batches, such that the total distance traveled for picking all batches is minimized. The total distance is determined by the picker routing strategy used in the warehouse. This paper addresses the OBP in rectangular warehouses consisting of two or more blocks with parallel aisles, expanding upon a branch-price-and-cut (BPC) approach previously applied to the OBP in single-block warehouses. The main extension lies in accommodating multi-block warehouse layouts, integrating both optimal and heuristic picker routing strategies. A key contribution of this work is the analysis of the monotonicity properties of routing strategies in multi-block configurations, which are crucial for the effective application of the BPC method. Computational results on publicly available benchmark instances with two-block layouts demonstrate that both the exact BPC and BPC-based heuristics outperform current state-of-the-art methods. Specifically, the joint order batching and picker routing problem, representing the OBP with optimal routing, is solved over three orders of magnitude faster than leading exact methods. Instances with up to 80 orders are solved to proven optimality for five different routing strategies, while BPC-based heuristics achieve superior performance on instances involving up to 500 orders.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"3 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145228797","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":"Prelim p. 2; First issue - Editorial Board","authors":"","doi":"10.1016/S0377-2217(25)00740-4","DOIUrl":"10.1016/S0377-2217(25)00740-4","url":null,"abstract":"","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"328 1","pages":"Page ii"},"PeriodicalIF":6.0,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145121244","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":"Order advancement in a multi-item two-echelon system: Theory and case study","authors":"Q. ten Hagen, M.C. van der Heijden, D.R.J. Prak","doi":"10.1016/j.ejor.2025.09.033","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.09.033","url":null,"abstract":"Motivated by a case at a large retail chain in the Netherlands, we study short-term order advancement in a multi-item, two-echelon system consisting of a distribution centre (DC) and many stores. Application of traditional inventory replenishment rules may lead to a strongly fluctuating workload for order picking, and thus capacity problems, at the DC. By advancing replenishments we can balance the workload at the DC without negative impact on the service levels towards the final customer, trading off backroom usage and handling of incoming orders under limited shelf space at the individual stores. We develop a performance evaluation method and various heuristics to find good order advancement solutions. We select the heuristic with the best trade-off between cost performance and computation time for large problem instances (i.e., hundreds of stores and thousands of stock keeping units). Application of this heuristic to case data from the retail chain shows around 10 % overall cost reduction. In particular, the capacity shortage at the DC – a major issue in our case study – is reduced by almost 67 % at the expense of more peaks in handling workload at the stores (42 % increase in order lines exceeding store capacity), and an increase of 7.6 % in backroom usage. Sensitivity analysis shows that a planning horizon of about two weeks performs best, and that the cost reduction potential is heavily influenced by the available shelf space.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"7 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145228833","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":"Integrated estimate-and-optimize decision trees learning for two-stage linear decision-making problems","authors":"Rafaela Ribeiro, Bruno Fanzeres","doi":"10.1016/j.ejor.2025.08.048","DOIUrl":"https://doi.org/10.1016/j.ejor.2025.08.048","url":null,"abstract":"Several decision-making under uncertainty problems found in industry and the scientific community can be framed as stochastic programs. Traditionally, these problems are addressed using a sequential two-step process, referred to as predict/estimate-then-optimize, in which a predictive distribution of the uncertain parameters is firstly estimated and then used to prescribe a decision. However, most predictive methods focus on minimizing forecast error, without accounting for its impact on decision quality. Moreover, practitioners often emphasize that their main goal is to obtain near-optimal solutions with minimum decision error, rather than least-error predictions. Therefore, in this work, we discuss a new framework for integrating prediction and prescription into the predictive distribution estimation process to be subsequently used to devise a decision. We particularly focus on decision trees and study decision-making problems representable as contextual two-stage linear programs. Firstly, we propose a workable framework along with a non-convex optimization model to account for the impact of the underlying decision-making problem on the predictive distribution estimation process. Then, we recast the non-convex model as a Mixed-Integer Programming (MIP) problem. Acknowledging the difficulty of the MIP reformulation to scale to large-scale instances, we devise a computationally efficient Heuristic strategy for the estimation problem leveraging the structure intrinsic to decision trees. A key feature of the proposed decision-making framework is its ability to instantly assess decisions by mapping new contexts to a leaf and retrieving the precomputed solution of the corresponding two-stage problem. A set of numerical experiments is conducted to illustrate the capability and effectiveness of the proposed framework using three distinct two-stage decision-making problems. We benchmark the proposed approach against prescriptions devised by various alternative frameworks. Five predict/estimate-then-optimize benchmarks that rely on commonly used predictive and distribution estimation methods and three benchmarks based on integrated predict-and-optimize decision-making processes are considered. We focus on evaluating solution quality and the computational performance of the MIP reformulation.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"113 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145228801","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}