Journal Information

Annals of Operations Research

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Impact Factor:
4.5
Publisher:
Springer
ISSN:
0254-5330
Viewed:
25197
Tracked:
4

Call For Papers

Annals of Operations Research is an academic journal published by Springer. (ISSN 0254-5330, impact factor 4.5).

Aims and scope The Annals of Operations Research publishes peer-reviewed original articles dealing with some aspects of operations research, including theory, practice, and computation. Submissions may include full-length research articles, short notes, expositions and surveys, reports on computational studies, and case studies of new or innovative practical applications. The Annals of Operations Research also publishes special volumes focusing on well-defined fields of operations research, ranging from the highly theoretical to the algorithmic and the very applied. Such volumes have one or more Guest Editors who are personally responsible for collecting the papers to appear in the volume, for overseeing the refereeing process, and for keeping the volume on schedule. Potential Guest Editors of new refereed volumes (proceedings of conferences, monographs, or focused collections of papers) in major OR areas are cordially invited to put forward their suggestions to the Editor-in-Chief. New submissions should be directed to the Editor-in-Chief, and manuscripts should be prepared following the "Instructions for Authors" on the journal’s homepage: www.springer.com/journal/10479. Manuscripts submitted for the Annals of Operations Research should report on original research, and should not have been previously published, or submitted for publication to any other journal. Officially cited as: Ann Oper Res
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Special Issues

Special Issue on Global Supply Chain Reconfiguration Under Tariff Uncertainty Submission Date: 2026-06-30 The reconfiguration of global supply chains has become increasingly urgent amid escalating tariff uncertainty and shifting international trade policies. Tariff-induced disruptions are reshaping sourcing strategies, manufacturing footprints, logistics networks, and market access worldwide. While tariff-related supply chain research is not new, today’s environment is marked by unprecedented levels of uncertainty and complexity. High tariff rates, retaliatory measures, and escalating trade tensions have created significant challenges for supply chain reconfiguration and management in practice. The unprecedented challenges of tariff uncertainty highlight the need for new decision-making models, offering significant opportunities to advance the literature and address pressing real-world challenges. This special issue of Annals of Operations Research invites high-quality contributions that develop and apply Operations Research (OR) and Artificial Intelligence (AI) methods to address the challenges and opportunities in global supply chain reconfiguration under tariff uncertainty. We welcome theoretical developments, methodological innovations, applied modelling studies, and quantitatively supported managerial insights. Interdisciplinary research that integrates OR, AI, supply chain management, and international economics, particularly with real-world case applications, is especially encouraged. Topics of Interest (include but are not limited to): • Supply network redesign and optimization under tariff uncertainty • Robust and stochastic optimization models for tariff-driven supply chain planning • Global supply chain reconfiguration under trade policy uncertainty • AI-powered dynamic supply chain adaptation and tariff response strategies • Dynamic production, sourcing, and logistics strategies facing tariff risks • Supply chain resilience and risk management for tariff disruptions • Logistics and warehousing for global e-commerce and omnichannel supply chains • Maritime network and logistics optimization with tariff impacts • Hybrid OR–machine learning for adaptive decision-making in global supply chains • Multi-echelon inventory management under fluctuating tariff policies • AI and data-driven methods for trade policy analysis and supply chain impacts • Optimization models and algorithms for large-scale global supply chain problems Manuscripts should be original, unpublished, and prepared according to Annals of Operations Research submission guidelines. Submissions are expected to have strong methodological contributions in OR and/or AI, with clear relevance to global supply chain reconfiguration under trade policy uncertainty
Last updated by Dou Sun in
Special Issue on Stochastic Optimization in Agriculture Submission Date: 2026-12-31 Stochastic optimization has seen many recent advances due to many reasons but mainly because of computer power, parallel programming, and AI hybridation. All this is impacting in the optimization of agricultural problems, either classical problems or new ones derived, for example, from the application of precision agriculture or precision livestock farming. In this context, Annals of Operations Research invites submissions to this special issue from any theoretical area of stochastic, robust, and distributionally robust optimization with applications in agriculture. The main topics of interest are, but not limited to: • Optimization techniques in agriculture under uncertainty • Advantages or inconveniences of stochastic optimization approaches • Practical stochastic optimization for decision making in agriculture • Agricultural and food supply chain management optimization • Surrogate models for stochastic optimization • New stochastic optimization methods in agriculture • New trends in stochastic optimization in the age of artificial intelligence • Multicriteria optimization methods under uncertainty • Scenario analysis in agriculture • Robust optimization and distributionally robust optimization • Product or suppliers selection and risk management
Last updated by Dou Sun in
Special Issue on Multiple Objective Programming and Goal Programming: Artificial Intelligence for Decision Making in Economic and Social Sciences Submission Date: 2027-06-30 This special issue aims to publish selected papers presented during the 16th International Conference on Multiple Objective Programming and Goal Programming (MOPGP'25: http://mopgp.org/) that will be held on 1–3 July 2025, in Varese, Italy. Contributions arising from papers presented at the conference should be substantially extended and cite the conference paper where appropriate. The special issue will also consider papers not presented during the conference. We seek original and unpublished work not currently under consideration in any other journal. The intersection of Multiple Objective Optimization (MOP), Goal Programming (GP), and Artificial Intelligence (AI) creates a robust framework for addressing complex decision-making challenges in Economic and Social Sciences. MOP provides structured methods to evaluate and prioritize conflicting objectives, while GP helps setting specific goals to be achieved by the decision maker. AI leverages data analytics and machine learning to process large datasets, revealing insights that improve the accuracy and the robustness of decision models and predictions. To this extent, this special issue will cover theories and application of MOP, GP, and AI focusing on, but not limited to, the following topics: 1. Advancements in Multiple Objective Programming Techniques 2. Goal Programming Techniques and Formulations 3. Goal Programming Approaches in Public Policy 4. AI-Enhanced Decision Support Systems for Resource Allocation 5. Data-Driven Methods in Economic and Social Decision-Making 6. Integrating Machine Learning with MOP 7. Multicriteria Deep Learning 8. Applications of MOP and GP in Sustainable Development 9. Real-Time Decision-Making Frameworks Using AI 10. Comparative Studies of MOP and GP in Various Contexts 11. Multi-Criteria Decision Analysis in Sustainable Economics 12. Multiple Criteria Decision Making in Environmental Economics 13. Optimization Models for Social Welfare 14. Behavioural Insights in Multi-Objective Decision-Making 15. Metaheuristics and Computational Methods in MOP 16. MOP and MCDM in AI applications 17. Innovative Applications to Economic and Social Sciences The scientific quality of the contributions is the main criterion in the selection process.
Last updated by Dou Sun in

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