Utku Karaca, Nurşen Aydın, Sinan Yıldırım, Ş. İlker Birbil
{"title":"Linear optimization with local differential privacy for resource sharing","authors":"Utku Karaca, Nurşen Aydın, Sinan Yıldırım, Ş. İlker Birbil","doi":"10.1007/s10479-026-07199-6","DOIUrl":"10.1007/s10479-026-07199-6","url":null,"abstract":"<div><p>This study examines a resource-sharing problem involving multiple parties that agree to use a set of capacities together. We start with modeling the whole problem as a mathematical program, where all parties are required to exchange information to obtain the optimal objective function value. This information bears private data from each party in terms of the coefficients used in the mathematical program. Moreover, the parties also consider the individual optimal solutions as private. In this setting, the concern for the parties is the privacy of their data and their optimal allocations. We propose a two-step approach to meet the privacy requirements of the parties. In the first step, we obtain a reformulated model that is amenable to a decomposition scheme. Although this scheme eliminates almost all data exchanges, it does not provide a formal privacy guarantee. In the second step, we provide this guarantee with a local differential privacy algorithm, which does not need a trusted aggregator, at the expense of deviating slightly from the optimality. We provide bounds on this deviation and discuss the consequences of these theoretical results. We also propose a novel modification to increase the efficiency of the algorithm in terms of reducing the theoretical optimality gap. The study ends with a numerical experiment on a planning problem that demonstrates an application of the proposed approach. As we work with a general linear optimization model, our analysis and discussion can be used in different application areas, including production planning, logistics, and revenue management.</p></div>","PeriodicalId":8215,"journal":{"name":"Annals of Operations Research","volume":"360 2-3","pages":"1007 - 1041"},"PeriodicalIF":4.5,"publicationDate":"2026-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10479-026-07199-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147828612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Mathematical programming for rapid pandemic vaccine distribution under capacity and lead-time constraints","authors":"Yun-Chia Liang, Dominico Laksma Paramestha","doi":"10.1007/s10479-026-07180-3","DOIUrl":"10.1007/s10479-026-07180-3","url":null,"abstract":"<div><p>Rapid mass vaccination is critical for curbing transmission during large-scale outbreaks, yet many optimization models emphasize cost or equity without explicitly shaping rollout speed. This study develops a deterministic time-oriented mathematical programming framework for national vaccine distribution that integrates multi-echelon flows, inter-echelon lead times, cold-chain capacity limits, and clinic service constraints. A time-weighted allocation objective is proposed to prioritize earlier coverage and is benchmarked against direct makespan minimization. Results show that the time-weighted formulation consistently increases early cumulative coverage while matching the final completion period obtained under makespan minimization across the tested benchmark instances, yielding a more favorable rollout trajectory without compromising completion time. Scenario experiments indicate that omitting supply availability, lead times, or clinic capacity can substantially underestimate rollout duration. In the Indonesia-based case study, vaccine availability, delivery delays, and vaccination throughput emerge as the dominant drivers of temporal performance, whereas expanding storage capacity provides limited marginal gains once feasibility is ensured. The findings highlight high-leverage interventions that strengthen upstream flow reliability and improve clinical throughput to accelerate population coverage under binding operational constraints.</p></div>","PeriodicalId":8215,"journal":{"name":"Annals of Operations Research","volume":"360 2-3","pages":"1209 - 1249"},"PeriodicalIF":4.5,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147828619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Addressing the unaddressed: a review of future research directions for post-pandemic supply chains","authors":"Kannan Govindan","doi":"10.1007/s10479-026-07204-y","DOIUrl":"10.1007/s10479-026-07204-y","url":null,"abstract":"<div><p>The COVID-19 pandemic created unprecedented disruptions across global supply chains, revealing significant vulnerabilities in production, distribution, healthcare logistics, and service systems. These disruptions highlighted the importance of analytical and operations research (OR) approaches in supporting timely and effective decision-making during large-scale health crises. This editorial introduces <i>Annals of Operations Research</i> special issue “Operations Research and Management Science Approaches for Fighting Against Epidemic Outbreaks Such as COVID-19,” which focuses on the application of OR methods to epidemic and pandemic-related challenges. This editorial first discusses the broader research landscape on epidemic logistics, healthcare operations, and supply chain disruptions resulting from infectious disease outbreaks. It then provides an overview of the contributions of the accepted papers included in this special issue, which address diverse topics such as testing strategies, healthcare resource allocation, vaccine distribution, supply chain risk management, policy evaluation, and the use of artificial intelligence and data-driven technologies in pandemic response. Because the special issue was developed while the COVID-19 pandemic was still unfolding, many of the contributions reflect real-time challenges faced by supply chains and public health systems. Building on these insights, this editorial also discusses emerging challenges and potential opportunities for supply chain management in the post-pandemic environment. Finally, several research questions and directions are proposed to support future studies aimed at strengthening resilience, improving preparedness, and enhancing decision-making capabilities for managing future epidemic and pandemic disruptions.</p></div>","PeriodicalId":8215,"journal":{"name":"Annals of Operations Research","volume":"360 1","pages":"1 - 13"},"PeriodicalIF":4.5,"publicationDate":"2026-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147755909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Shapley value for games with expanded coalitions","authors":"M. J. Albizui, M. Cerny, J. M. Zarzuelo","doi":"10.1007/s10479-026-07159-0","DOIUrl":"10.1007/s10479-026-07159-0","url":null,"abstract":"<div><p>Derks and Peters (1993) introduce games with restricted coalitions defined by means of restrictions, which are monotonic projections of the set of players that assign to each coalition a subcoalition. They introduce a Shapley value considering these projections. In our work, we also consider a monotonic projection of the set of players, but instead of taking subcoalitions of coalitions, we take coalitions that contain them. That is, coalitions are expanded. In this way, we model situations in which some players are necessary to make a coalition effective. We give a Shapley value in this framework and obtain two axiomatic characterizations that determine endogenously the projection that expands the coalitions. In the first characterization, we employ a generalization of a monotonicity axiom used by (Young, (1985)) to characterize the Shapley value. In the second one, a dummy player axiom is required, together with additivity. Additionally, we provide an axiomatic characterization of the value introduced by Derks and Peters (1993), employing a suitably adapted dummy player axiom.</p></div>","PeriodicalId":8215,"journal":{"name":"Annals of Operations Research","volume":"360 2-3","pages":"685 - 701"},"PeriodicalIF":4.5,"publicationDate":"2026-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10479-026-07159-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147828522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Giuseppe Scandurra, Alfonso Carfora, Antonio Thomas, Cecilia Camporeale
{"title":"Predicting energy poverty using household budget survey: a machine learning approach","authors":"Giuseppe Scandurra, Alfonso Carfora, Antonio Thomas, Cecilia Camporeale","doi":"10.1007/s10479-026-07187-w","DOIUrl":"10.1007/s10479-026-07187-w","url":null,"abstract":"<div><p>Energy poverty (EP) is considered an urgent challenge, intensified by rising energy costs, economic inequality, and the transition toward green energy, which involves many Western countries. By referring to Italy, this study employs machine learning algorithms (MLAs) to predict and classify EP using official Household Budget Survey (HBS) data. To evaluate EP, the study compares several MLAs alongside three expenditure-based indicators proposed in three seminal articles by Hills, Faiella and Lavecchia, and Betto et al. Among these, the indicator developed by Betto et al., which accounts for regional and socioeconomic disparities, consistently outperforms the others across all MLAs, demonstrating higher accuracy, precision, and recall. This ensures a more comprehensive identification of energy-poor households. The analysis highlights the significant impact of data imbalance on model performance, emphasizing the need for techniques such as SMOTE and undersampling. The superior performance of the Betto et al. indicator underscores its potential as a benchmark for EP measurement, providing a valuable tool for policymakers to design targeted interventions, allocate resources effectively, and support a just and sustainable energy transition. The study reinforces the importance of dynamic, data-driven approaches to address EP, and calls for improved data collection to enhance prediction accuracy and policy effectiveness.</p></div>","PeriodicalId":8215,"journal":{"name":"Annals of Operations Research","volume":"360 2-3","pages":"1073 - 1100"},"PeriodicalIF":4.5,"publicationDate":"2026-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10479-026-07187-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147828613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Student assignments with preferences and maximum diversity","authors":"Arne Schulz","doi":"10.1007/s10479-026-07189-8","DOIUrl":"10.1007/s10479-026-07189-8","url":null,"abstract":"<div><p>The paper considers the assignment of students to seminars regarding three hierarchical objectives: maximizing the students’ preferences, maximizing the within seminar diversity, minimizing the between seminar diversity variation. While the first objective pictures the students, preferences, the second and third picture the school’s preference of having comparable seminar groups. To reach this aim the paper extends the well-known Maximally Diverse Grouping Problem and its balanced version by the first objective, the students’ interests. The students’ interests are pictured by a preference sequence the students have for the offered seminars, e.g. because of the scheduled time, the topic or the lecturer. We present solution approaches that include properties from game theory in the assignment and result in an assignment of students to seminars including the students’ as well as the school’s preferences. Our results show that the presented solution approaches are able to solve instances of practical relevant size within half an hour (close to) optimality. Furthermore, in our artificial test instances, including student preferences in the assignment only led to a small reduction of the maximal diversity for instances of realistic size (2–3% difference for seminars with 20 students).</p></div>","PeriodicalId":8215,"journal":{"name":"Annals of Operations Research","volume":"360 2-3","pages":"1101 - 1124"},"PeriodicalIF":4.5,"publicationDate":"2026-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10479-026-07189-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147828593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Lifted formulations for the Target Visitation problem","authors":"Ali Balma","doi":"10.1007/s10479-026-07168-z","DOIUrl":"10.1007/s10479-026-07168-z","url":null,"abstract":"<div><p>In the present paper, we address the target visitation problem, aiming to deliver first-aid medicine and necessary food to regions (called targets) suffering from natural disasters or conflicts. In addition, it has many applications for security and surveillance purposes. It consists of planning the tour of an unmanned aerial vehicle, which visits each target once. The objective considers the mutual priorities between the targets and the respective distances. From a theoretical point of view, the problem combines the traveling salesman and the linear ordering problems. We present formulations adapted and lifted from the literature of the traveling salesman. We enhance two particular models. We apply the lifting technique to the first model, which is related to a well-known node-based formulation. We further strengthen it by carrying out a partial projection of an existing multi-commodity flow formulation of the traveling salesman problem in an extended space. Alternatively, we perform a partial Reformulation-Linearization Technique to the same multicommodity flow-based model and obtain a stronger new formulation. For the latter, we develop a solution approach based on a cutting-plane fashion that successfully provided optimal solutions to all benchmark instances for the first time.</p></div>","PeriodicalId":8215,"journal":{"name":"Annals of Operations Research","volume":"360 2-3","pages":"879 - 914"},"PeriodicalIF":4.5,"publicationDate":"2026-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147828608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"New DEA models for business partnerships: evidence from nonhomogeneous banking","authors":"Gholam R. Amin, Mustapha Ibn Boamah","doi":"10.1007/s10479-026-07167-0","DOIUrl":"10.1007/s10479-026-07167-0","url":null,"abstract":"<div><p>Businesses often have resource constraints in their efforts to address market needs, and as a result they seek strategic alliances and various partnerships with other businesses to achieve their shared objectives. Homogeneity among decision making units (DMUs) is assumed in the standard data envelopment analysis (DEA), but there are many real-life situations where DMUs make different set of outputs that nullifies the homogeneity assumption. Moreover, business partnerships may involve DMUs that are nonhomogeneous to achieve synergies, create enhanced value, and improve competitiveness. This paper introduces new DEA models for determining beneficial business partnerships between nonhomogeneous DMUs under input and output orientations. These models reveal the mutual gains of efficiency improvement for participating partners in nonhomogeneous business partnerships by redistributing partners’ resources. The paper also presents a novel application in banking with non homogeneity in products and services, to demonstrate the practicability of the developed DEA models in this study. The findings show how partnerships between banks with nonhomogeneous activities can enhance their efficiency.</p></div>","PeriodicalId":8215,"journal":{"name":"Annals of Operations Research","volume":"360 2-3","pages":"703 - 722"},"PeriodicalIF":4.5,"publicationDate":"2026-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147828524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Martina Luzzi, Francesca Guerriero, Giusy Macrina, Chefi Triki
{"title":"Restaurant revenue management through combinatorial auctions","authors":"Martina Luzzi, Francesca Guerriero, Giusy Macrina, Chefi Triki","doi":"10.1007/s10479-026-07198-7","DOIUrl":"10.1007/s10479-026-07198-7","url":null,"abstract":"<div><p>Booking a table in some popular restaurants, particularly in certain big cities, is becoming increasingly challenging. The number of requests to eat in those restaurants exceeds the available supply, resulting in a shortage of seating capacity. In recent years, the market for resale of restaurant reservations has emerged as possible solution to this problem. However, this practice does not offer to restaurateurs any protection on the certainty of booking, is unfair to customers, and can lead to a high no-show rate. This work presents an innovative framework for restaurant revenue management, which aims to optimise revenues by managing bookings at restaurants. Particularly, the concept of combinatorial auction is applied to allocate tables and menus to the customers who participate in the auction through a web platform. The winner determination problem is solved in order to assign requests to the bidding customers. Furthermore, a procedure to address the bid generation problem, based on realistic data, is also proposed. The scalability of the model is addressed with an extensive test phase. The applicability of this novel approach is also tested on a real Michelin-starred restaurant. Results of computational experiments suggest that the profitability of this practice has the potential to revolutionize the restaurant reservations sector in the near future.</p></div>","PeriodicalId":8215,"journal":{"name":"Annals of Operations Research","volume":"360 2-3","pages":"1043 - 1072"},"PeriodicalIF":4.5,"publicationDate":"2026-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10479-026-07198-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147828614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Agency theory and higher-order risk changes","authors":"Claudio A. Bonilla, Hervé Roche, Marcos Vergara","doi":"10.1007/s10479-026-07081-5","DOIUrl":"10.1007/s10479-026-07081-5","url":null,"abstract":"<div><p>We study the classic agency model when the suitable ordering of risky prospects is better represented by higher- rather than first-order risk changes. We derive conditions on preferences under which the principal would want a greater effort level provided by the agent than the one provided under the second-best sharing rule. Our characterization attempts to bridge the gap between current developments in the economic theory of risk and uncertainty and the classical agency model. Finally, we apply our findings to CARA, CRRA and HARA preferences.</p></div>","PeriodicalId":8215,"journal":{"name":"Annals of Operations Research","volume":"360 2-3","pages":"915 - 950"},"PeriodicalIF":4.5,"publicationDate":"2026-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147828609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}