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Journals in Decision sciences

Our Decision Sciences titles care essential reading for students and professionals, and cover key topics in decision support systems, and global logistics, among other areas of research and practice

  • Computers & Operations Research

    • ISSN: 0305-0548
    Computers & Operations Research is a privileged forum for state-of-the-art work exploring the theory and practice of Operations Research (OR) intertwined with advanced computational methodologies. The journal publishes high-quality innovative and impactful research articles in theories, modeling, algorithms, and applications of Operations Research.Since its first volume was printed in 1974, the journal has promoted different OR application areas that include but are not limited to Transportation, Logistics, Manufacturing, and Supply Chain Management. The journal has also triggered new trends in OR models and techniques such as Data Analytics, Decision-making under Uncertainty, and Behavioral OR. A strong focus has been put on recent advances in Statistics, Data Science, and Machine Learning.The form, content, and language of the articles should take cognizance of the breadth of applications covered by OR and of the consequent fact that many readers may not be experts in the scientific field to which the computer and operations research techniques are applied by the author. In particular, the abstract should concisely describe:1. the investigated problem(s), 2. the theoretical or methodological contribution, and 3. the insights.The journal is structured around seven major areas which, nonetheless, are not disjointed:Transport... and Supply Chains; Production and Scheduling; Decision-Making under Uncertainty and Data Analytics; Optimization—Exact Methods; Optimization—Approxi... Methods; Machine Learning and Data Science. The journal also publishes state-of-the-art surveys and best practice guides in Analytics, Operations Research, and Management Science. These articles are printed in a special section, “Surveys in Operations Research and Management Science”. Submissions can focus on theory or applications of OR/MS and can be of several types, including but not limited to: 1. Results that are considered standards by experts in the community but which have not been documented in textbooks; 2. Standard results which have been, in some way, streamlined, such as, for example, new proof techniques leading to more elegant derivations of known results; 3. New developments in methodology or new application areas ('hot topics'). A survey should be critical with respect to the existing knowledge and should focus on computational and algorithmic aspects. The journal publishes focused issues on topics of interest related to its editorial mission. Such issues typically contain between six and twelve articles. They are put together within an eighteen-month period under the responsibility of one or several guest editors. Prospective guest editors are encouraged to contact the Editor-in-chief.Full... reproducible results are core for papers accepted for publication in the journal. Hence, authors should grant full access to the data and codes underlying their work. Further information on different possibilities to accomplish this can be found at https://www.scienced... Best Paper AwardEvery year, the journal’s editors select one paper to receive the “CAOR Annual Best Paper Award”. The paper will be made free-to-view for one year, thus receiving privileged visibility. The winning and the runner-up papers will also be highlighted on the website in the “Editor’s Choice” section, staying there for one year.Further Information for authorsIt is the responsibility of the authors to ensure that the submitted manuscripts are written using proper English, that possible grammatical or spelling errors are eliminated and that the text conforms to correct scientific English. Submissions that do not satisfy these criteria may be rejected without being sent to reviewers.All full-length research papers published in the journal must demonstrate constructive algorithmic complexity and extensive numerical experiments. Numerical illustrations (examples) are not sufficient: the numerical experiments must have a scientific value of their own, particularly with comparisons to other approaches. The use of real-world data is also valued. In CAOR, (meta)Heuristics other than well-established algorithms such as evolutionary algorithms or ant colony optimization must be described in metaphor-free language. This is a way to ensure that they are immediately comparable to existing algorithms. The Harvard style is adopted in the journal for the bibliography. Authors should consider this while preparing their manuscripts, especially when preparing tables and charts involving bibliography references.The highly innovative contributions targeted by the journal prevent it from endorsing papers that present long and unsolvable formulations for variants or extensions of existing problems and then resort to a well-established approximate method to find approximate solutions. CAOR does not endorse papers emerging in the context of warfare activities planning. The authors working in that and related fields should look for specialized journals.
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  • Operations Research, Data Analytics and Logistics

    • ISSN: 2211-6923
    Healthcare Operations – Humanitarian Logistics – Medical Decision Support - Pharmaceutical OperationsOperations Research, Data Analytics, and Logistics (ORDAL) focuses on understanding and implementing better healthcare for society using quantitative methodology. The core application area is healthcare in the broadest sense. The journal focuses primarily on Healthcare Operations, Humanitarian Logistics, Medical Decision Support, and Pharmaceutical Operations. ORDAL publishes high-quality quantitative approaches for decision-making and decision support in healthcare from researchers and practitioners. ORDAL encourages contributions related to typical problem areas of healthcare, such as acute care, hospital care, specialist care, primary care, home care, long-term care, emergency care, humanitarian care, etc. Contributions can focus on the whole value chain in healthcare, tackling core and support processes. For instance, topics of interest are capacity planning, layout planning, operating room planning, surgical scheduling, patient logistics, appointment scheduling, medical decision-making, etc. ORDAL welcomes contributions, if suitable to the journal’s objectives, in health informatics, health decision support systems, health analytics, health policy, health management, health economics, population health etc. ORDAL stimulates contributions advancing the current state-of-the-art and applying quantitive methodology, such as mathematical programming, stochastic optimization, simulation, data science, artificial intelligence, machine learning, etc., to relevant healthcare-related problems. ORDAL inspires using real-world data in case studies and/or numerical experiments. Ideally, the source data is publicly available.In addition to original research articles, ORDAL publishes, upon reasonable request to the Editor-in-Chief, papers in the following two categories:1) Review papers: ORDAL provides maximum benefit to researchers and practitioners who are genuinely interested in operations research, data analytics, and logistics for better healthcare. Review papers should focus on emerging topics in healthcare and are by invitation only.2) Special Issues (SIs): ORDAL publishes special issues on topics of interest related to its editorial mission. SIs typically contain between six and twelve papers and have a dedicated focus area. One or several guest editors, experts in the field, are responsible for the SI. However, the final decision on all papers will be made by the Editor-in-Chief. Potential guest editors should send a prospective call for papers and informative CVs for the guest editors. Sis should focus on emerging topics in healthcare and are by invitation only.
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  • Operations Research, Data Analytics and Logistics

    • ISSN: 3050-7847
    Healthcare Operations – Humanitarian Logistics – Medical Decision Support - Pharmaceutical OperationsOperations Research, Data Analytics, and Logistics (ORDAL) focuses on understanding and implementing better healthcare for society using quantitative methodology. The core application area is healthcare in the broadest sense. The journal focuses primarily on Healthcare Operations, Humanitarian Logistics, Medical Decision Support, and Pharmaceutical Operations. ORDAL publishes high-quality quantitative approaches for decision-making and decision support in healthcare from researchers and practitioners. ORDAL encourages contributions related to typical problem areas of healthcare, such as acute care, hospital care, specialist care, primary care, home care, long-term care, emergency care, humanitarian care, etc. Contributions can focus on the whole value chain in healthcare, tackling core and support processes. For instance, topics of interest are capacity planning, layout planning, operating room planning, surgical scheduling, patient logistics, appointment scheduling, medical decision-making, etc. ORDAL welcomes contributions, if suitable to the journal’s objectives, in health informatics, health decision support systems, health analytics, health policy, health management, health economics, population health etc. ORDAL stimulates contributions advancing the current state-of-the-art and applying quantitive methodology, such as mathematical programming, stochastic optimization, simulation, data science, artificial intelligence, machine learning, etc., to relevant healthcare-related problems. ORDAL inspires using real-world data in case studies and/or numerical experiments. Ideally, the source data is publicly available.In addition to original research articles, ORDAL publishes, upon reasonable request to the Editor-in-Chief, papers in the following two categories:1) Review papers: ORDAL provides maximum benefit to researchers and practitioners who are genuinely interested in operations research, data analytics, and logistics for better healthcare. Review papers should focus on emerging topics in healthcare and are by invitation only.2) Special Issues (SIs): ORDAL publishes special issues on topics of interest related to its editorial mission. SIs typically contain between six and twelve papers and have a dedicated focus area. One or several guest editors, experts in the field, are responsible for the SI. However, the final decision on all papers will be made by the Editor-in-Chief. Potential guest editors should send a prospective call for papers and informative CVs for the guest editors. Sis should focus on emerging topics in healthcare and are by invitation only.
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  • Automatica

    • ISSN: 0005-1098
    A journal of IFAC, the International Federation of Automatic Control, Automatica is a leading archival publication in the field of systems and control. The field today encompasses a broad set of areas and topics, and is thriving not only within itself but also in terms of its impact on other fields, such as communications, computers, biology, energy and economics. After being founded in 1963, Automatica became a journal of the International Federation of Automatic Control (IFAC) in 1969. Since its inception, Automatica has kept abreast with the evolution of the field over the years, and has emerged as a leading publication driving the trends in the field.Automatica features a characteristic blend of theoretical and applied papers of archival, lasting value, reporting cutting edge research results by authors across the globe. It features articles in distinct categories, including regular, brief and survey papers, technical communiqués, correspondence items, as well as reviews on published books of interest to the readership. It occasionally publishes special issues on emerging new topics or established mature topics of interest to a broad audience.Automatica solicits original high-quality contributions in all the categories listed above, and in all areas of systems and control interpreted in a broad sense and evolving constantly. Papers should be submitted using the on-line review management system Pampus www.autsubmit.com.
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  • Transportation Research Part E: Logistics and Transportation Review

    • ISSN: 1366-5545
    Transportation Research Part E: Logistics and Transportation Review (TR-E) is differentiated from its sister journals (TR-A, TR-B, TR-C, TR-D, and TR-F). As reflected in their title, the commonality between these journals is the focus on ‘Transportation,’ but TR-E is differentiated by specializing in ‘Logistics.’ Of course, it is widely accepted that transportation is undoubtedly one of the most critical components of logistics. TR-E publishes informative and high-quality articles drawn from across the spectrum of logistics components. The related research studies are multi-disciplinary and include (i) hard/ classic logistics research, such as transportation, material handling, packaging, warehousing, inventory, and handling, and so on (ii) soft logistics research by adding Operations Management (OM) and Supply Chain Management (SCM) concepts, tools, and philosophies to the classic logistics, such as sustainability, risk and disruption, circular economy, and artificial intelligence.There are no limitations to the research methods utilized. Therefore, various research methods can be used, such as analytical (e.g., operations research techniques including game theory, queuing theory, dynamic programming, linear, integer, and nonlinear programming), quantitative and qualitative empirical research (e.g., time series, regression, microeconomics), simulation, mixed research methods (e.g., combining surveys and case studies with quantitative data analysis), experimental research (e.g., controlled experiments, lab experiments, and field experiments), case studies (e.g., in-depth analysis), machine learning, artificial intelligence and network analysis (e.g., graph theoretic concept).
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  • Journal of Engineering and Technology Management

    • ISSN: 0923-4748
    The Journal of Engineering and Technology Management (JET-M) is an international scholarly refereed research journal which aims to promote the theory and practice of technology, innovation, and engineering management.The journal links engineering, science, and management disciplines. It addresses the issues involved in the planning, development, and implementation of technological capabilities to shape and accomplish the strategic and operational objectives of an organization. It covers not only R&D management, but also the entire spectrum of managerial concerns in technology-based organizations. This includes issues relating to new product development, human resource management, innovation process management, project management, technological fusion, marketing, technological forecasting and strategic planning.The journal provides an interface between technology and other corporate functions, such as R&D, marketing, manufacturing and administration. Its ultimate goal is to make a profound contribution to theory development, research and practice by serving as a leading forum for the publication of scholarly research on all aspects of technology, innovation, and engineering management.
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  • Research in Social Stratification and Mobility

    • ISSN: 0276-5624
    The Official Journal of the ISA RC28 on Social Stratification and MobilityThe study of social inequality is and has been one of the central preoccupations of social scientists. Research in Social Stratification and Mobility is dedicated to publishing the highest, most innovative research on issues of social inequality from a broad diversity of theoretical and methodological perspectives. The journal is also dedicated to cutting edge summaries of prior research and fruitful exchanges that will stimulate future research on issues of social inequality.
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  • Transportation Research Part A: Policy and Practice

    • ISSN: 0965-8564
    Transportation Research: Part A considers papers dealing with policy analysis (design, formulation and evaluation); planning; interaction with the political, socioeconomic and physical environments; and management and evaluation of transport systems. Topics may be approached from any discipline or perspective: economics, engineering, psychology, sociology, urbanism, etc., but must have a clear policy concern or be of interest for practice, and must be based on solid research and good quality data. The journal is international, and places equal emphasis on the problems of industrialized and non-industrialized regions.Part A's aims and scope are complementary to Transportation Research Part B: Methodological, Part C: Emerging Technologies and Part D: Transport and Environment. Part E: Logistics and Transportation Review. Part F: Traffic Psychology and Behaviour. The complete set forms the most cohesive and comprehensive reference of current research in transportation science.
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  • Journal of Rail Transport Planning & Management

    • ISSN: 2210-9706
    Affiliated with the International Association of Railway Operations ResearchJournal of Rail Transport Planning & Management aims to stimulate the quality of service for railway passengers and freight customers by improving the knowledge on effectiveness and efficiency of capacity management, timetabling, management and safety of railway operations. It covers the whole range of light rail, metro, heavy and high-speed railway systems. The journal will create a platform for regular transfer of knowledge, new tools and discussion of innovative contributions regarding the analysis of passenger and freight railway transport, estimation of traffic demand and capacity, design of timetables, scheduling of trains and crews, dispatching, signalling, train control, automatic train operation, optimal use of rolling stock and energy in order to increase the efficiency and competitiveness of passenger and freight transport.The journal presents innovative theoretical approaches, high-tech concepts, new technological, financing and business management models and tools that can provide higher flexibility, performance and punctuality of trains operating on dedicated lines and in heterogeneous networks. Journal of Rail Transport Planning & Management integrates the expertise from different scientific disciplines as physical planning, transport modelling, traffic analysis, (system) engineering, mathematics, physics, computer science, economics and (transport) policy analysis.The articles accepted comprise generic theoretical research projects, original concise transport and business plans, pilot technical and economic feasibility analyses, as well as genuine impact assessment studies in the railway domain.Journal of Rail Transport Planning & Management supports the development of a “Network of Excellence” in the field of railway system planning, operations research, business development, traffic control and operations management. It brings together academics and professionals who advise governments, railway infrastructure managers, train operating companies and industrial suppliers on promising and successful innovation strategies for railway transport policy, lines, networks, operations and management.
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  • Operations Research Letters

    • ISSN: 0167-6377
    Operations Research Letters (ORL) is committed to the rapid review and fast publication of short articles on all aspects of operations research and analytics. ORL welcomes pure methodological papers and applied papers with firm methodological grounding. All articles are restricted to at most eight journal pages, with the option to relegate proofs and additional material to an online appendix. The main criteria for the papers to be published are quality, originality, relevance, and clarity. The journal's traditional strength is in methodology, including theory, modelling, algorithms, and computational studies. Please find below a full description of the areas covered by the journal.Area EditorsApproximation Algorithms for Combinatorial Optimization Problems Area Editor: Leah Epstein Associate Editors: M. Chrobak, K. Elbassioni, M. Feldman, J. Hurink, N. Olver, J. Sgall, J. Verschae The area covers all issues relevant to the development of efficient approximate solutions to computationally difficult problems. This includes worst case analysis or competitive analysis of approximation algorithms, and complexity results.Submissions can be articles consisting of theoretical work in the area, or articles combining significant theoretical contributions of mathematical flavor with computational investigations of heuristic approaches. Articles in the area of discrete optimization that do not belong to the scope of other areas may be submitted to this area as well.Computational Social Science Area Editor: Vianney Perchet Associate Editors: A. Drutsa, P. Mertikopoulos, R. Smorodinsky This area publishes papers focusing on data-driven procedures, either from a theoretical or an applied perspective, in operation research, games, economics and other social science. The scope includes: sample/computational complexity of mechanisms, learning in games/OR/social science, empirical solutions with AI algorithms (such as, but not limited to, deep learning techniques) of complex problems, etc. Continuous Optimization Area Editor: Hector Ramirez Associate Editors: M.F. Anjos, L.M. Briceno, D. Dadush, G. Eichfelder, D. Jiang, D. Orban, F. Schoen Papers in all fields of continuous optimization that are relevant to operations research are welcome. These areas include, but are not restricted to, linear programming, nonlinear programming (constrained or unconstrained, convex or nonconvex, smooth or nonsmooth, finite or infinite-dimensional... complementarity problems, variational inequalities, bilevel programming, and mathematical programs with equilibrium constraints. Financial Engineering Area Editor: Ning Cai Associate Editors: X. He, D. Mitchell Financial engineering utilizes methodologies of optimization, simulation, decision analysis and stochastic control to analyse the effectiveness and efficiency of financial markets. This area is interested in papers that innovate in terms of methods or that develop new models which guide financial practices. Examples include but are not limited to Fintech, financial networks, market microstructure, derivative pricing and hedging, credit and systemic risk, energy markets, portfolio selection. Game Theory Area Editor: Tristan Tomala Associate Editors: S. Beal, V. Ihele, D.W.K. Yeung, G. Zaccour This area publishes papers which use game theory to analyze operations research models or make theoretical contributions to the theory of games. The scope includes (but is not limited to): cooperative and non-cooperative games, dynamic games, mechanism and market design, algorithmic game theory, games on networks, games of incomplete information. Graphs & Networks Area Editor: Gianpaolo Oriolo Associate Editors: F. Bonomo, Y. Faenza, Z. Friggstad, L. Sanita The area seeks papers that apply, in original and insightful ways, discrete mathematics to advance the theory and practice of operations research, as well as those reporting theoretical or algorithmic advances for the area. Of particular, but not exclusive, interest are papers devoted to novel applications, telecommunications and transportation networks, graphs and web models and algorithms. Inventory and Supply Chain Optimization Area Editor: Sean Zhou Associate Editors: H. Abouee Mehrizi, A. Burnetas, X. Gong, Q. Li, J. Yang The area welcomes innovative papers focused on inventory control and supply management. Examples of topics include, but are not limited to, optimal sourcing, inventory and assortment selection, pricing and inventory optimization, capacity planning, multi-item/echelon systems, algorithms and bounds, near-optimal or asymptotic optimal solutions, and incentive design. Mixed Integer Optimization Area Editor: Marc Pfetsch Associate Editors: R. Fukasawa, L. Liberti, J.P. Vielma, G. Zambelli All submissions advancing the theory and practice of mixed integer (linear or nonlinear) programming like novel techniques and algorithmic approaches in convex relaxations, branch and cut, polyhedral combinatorics and theory driven heuristics are welcome. Case studies may be considered if they contribute to the general methodology. Operations Management Area Editor: Mahesh Nagarajan Associate Editors: L. Chu, Y. Ding, N. Golrezaei, T. Huh, D. Saban, C. Shi, L. Zhu The OM department aims to publish short, focused high quality research in the area of operations management, broadly the field of operations research applied to management problems. We welcome papers that use a wide variety of methodologies, both descriptive as well as prescriptive in nature including optimization, applied probability, simulation, and game theory. Scheduling Area Editor: Marc Uetz Associate Editors: B. Moseley, E. Pesch, R. Van Stee We seek original and significant contributions to the analysis and solution of sequencing and scheduling problems. This includes structural and algorithmic results, in particular optimization, approximation and online algorithms, as well as game theoretic modeling. All results are welcome as long as the relevance of a problem and significance of the contribution is made compellingly clear. Stochastic Models and Data Science Area Editor: Henry LamAssociate Editors: H. Bastani, J. Dong, K. Murthy, I. Ryzhov, Y. Zhou The area seeks papers broadly on the interplay between operations research and machine learning and statistics where stochastic variability and uncertainty play a crucial role. The area values both papers that develop or utilize stochastic analysis and computation in data science problems, including but not limited to reinforcement learning, stochastic iterative algorithms for model estimation or training, probabilistic analysis of statistical and machine learning tools, sampling and Monte Carlo methods, and also papers that integrate learning or statistical techniques into stochastic modeling to enhance prediction or decision-making for a wide variety of systems. Stochastic Networks and Queues Area Editor: Harsha HonnappaAssociate Editors: R. Roet-Green, E. Ozkan, W. Wang, Y. ZhaoThe area seeks papers that contribute to the modeling, analysis or innovative application of stochastic networks or queues. Work submitted should propose original models and develop novel analytical or computational methods more than incremental extensions. Examples of relevant application areas include but are not limited to supply chain management, manufacturing, financial engineering, healthcare, revenue management, service operations, telecommunications, sharing economy, online markets and public sector operations research. Application-oriented papers should demonstrate direct practical impact and have a strong methodological component as well.Stochastic Optimization and Machine Learning Area Editor: Angelos Georghiou Associate Editors: M. Bodur, M. Claus, E. Feinberg, P. Vayanos The Stochastic Optimization and Machine Learning area of Operations Research Letters solicits original articles that generate novel insights into problems that arise in optimization under uncertainty and in machine learning. The focus is broad and encompasses, among others, stochastic (dynamic) programming, (distributionally) robust optimization, data-driven optimization as well as the interface of machine learning with traditional areas of operations research. Successful submissions in this area are expected to make a clear and meaningful academic contribution, which may be through the study of new problems, models, solution techniques, performance analysis and convincing and reproducible numerical evaluations.
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