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Journals in Mathematics

The Mathematics collection presents a range of foundational and advanced research content across applied and discrete mathematics, including fields such as Computational Mathematics; Differential Equations; Linear Algebra; Modelling & Simulation; Numerical Analysis; Probability & Statistics.

  • International Journal of Forecasting

    • ISSN: 0169-2070
    Official Publication of the International Institute of ForecastersThe International Journal of Forecasting is the leading journal in its field. It is the official publication of the International Institute of Forecasters (IIF) and shares its aims and scope. More information about the IIF may be found at https://www.forecast... International Journal of Forecasting publishes high quality refereed papers covering all aspects of forecasting. Its objective (and that of the IIF) is to unify the field, and to bridge the gap between theory and practice, making forecasting useful and relevant for decision and policy makers. The journal places strong emphasis on empirical studies, evaluation activities, implementation research and ways of improving the practice of forecasting. It is open to many points of view and encourages debate to find solutions for problems facing the field.Topics covered in the International Journal of Forecasting:• Economic and econometric forecasting • Marketing forecasting • New products forecasting • Financial forecasting • Production forecasting • Technological forecasting • Forecasting applications in business, government, and the military • Demographic forecasting • Energy forecasting • Climate forecasting • Crime forecasting • Seasonal adjustments and forecasting • Time series forecasting • Legal and political aspects of forecasting • Implementation of forecasting • Judgmental/psycholog... aspects of forecasting • Impact of forecast uncertainty on decision making • Organizational aspects of forecasting • Sport forecasting • Machine Learning forecasting • Forecasting methodology • Election forecasting • Big data forecasting Features of the IJF include research papers, research notes, discussion articles, book reviews, editorials and letters.Data and computer programs associated with articles published in the International Journal of Forecasting are provided as online supplements on ScienceDirect.Object... To ensure fairness and objectivity, double-blind reviewing will be used.Replication studies The IJF encourages replication studies, especially of highly cited papers. See Encouraging replication and reproducible research (an editorial published in 2010) for further information. A replication study that confirms that a published paper can be successfully replicated would normally be quite short (about a page is often sufficient to describe what calculations and comparisons have been done). Where a previously published paper has not been successfully replicated, more details are required to explain how the results differ from those previously published.
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  • Journal of the Franklin Institute

    • ISSN: 0016-0032
    Engineering and Applied MathematicsAs the second oldest continuously published American journal devoted to science and technology, the Journal of The Franklin Institute has an established reputation for publishing high quality papers in the field of engineering and applied mathematics.As a peer-reviewed journal, its goal is to promote inspiring advancements in the fields of engineering and applied mathematics by voices from the scientific and academic communities.As of 2022, the Journal of The Franklin Institute has expanded its content focus to include research under the field of Data Science. The journal welcomes high quality original manuscript submissions that fall under three main topic areas:Control Systems Complex Networks & Dynamic SystemsData Science & Signal ProcessingAside from original manuscripts, the Journal of The Franklin Institute encourages authors to put forth evolving new special issue proposals for publication, provided they fall broadly within the scope of the journal. Special issues with a strong conceptual foundation in newly evolving topics are continuously planned for future issues. These special issues are reviewed based on their novelty and possible lasting value to the field of study.
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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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  • Advances in Engineering Software

    • ISSN: 0965-9978
    Aerospace • Civil • Environmental • Mechanical and Structural EngineeringIncluding Computing Systems in EngineeringThe objective of this journal is to communicate recent and projected advances in computer-based engineering techniques. The fields covered include mechanical, aerospace, civil and environmental engineering, with an emphasis on research and development leading to practical problem-solving.The scope of the journal includes: • Innovative computational strategies and numerical algorithms for large-scale engineering problems • Analysis and simulation techniques and systems • Model and mesh generation • Control of the accuracy, stability and efficiency of computational process • Exploitation of new computing environments (eg distributed hetergeneous and collaborative computing) • Advanced visualization techniques, virtual environments and prototyping • Applications of AI, knowledge-based systems, computational intelligence, including fuzzy logic, neural networks and evolutionary computations • Application of object-oriented technology to engineering problems • Intelligent human computer interfaces • Design automation, multidisciplinary design and optimization • CAD, CAE and integrated process and product development systems • Quality and reliabilityThe journal publishes research papers, survey papers on key application areas, short communications and technical notes, discussions, software reviews and book reviews. A conference calendar is also included – entries welcome.Related conferences are listed under 'Related publications'.
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  • Journal of Econometrics

    • ISSN: 0304-4076
    The Journal of Econometrics serves as an outlet for important, high quality, new research in both theoretical and applied econometrics. The scope of the Journal includes papers dealing with identification, estimation, testing, decision, and prediction issues encountered in economic research. Classical Bayesian statistics, experimental design, and machine learning methods are decidedly within the range of the Journal's interests.There are two types of submissions 1. Regular (open submissions):full length papers, orshort papers less than 15 pages.A Themed issue is a collection of regular (open)submissions on the same topic proposed and/or approved by the Co-Editors. A full list of Themed Issues currently open for submission can be found here. Proposals for themed issues can be sent to journalofeconometric... Invited papers The Co-Editors may invite contributions to“how to” papers on topics of interest in applied economics.“Annals Issues” to mark special events.
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  • Engineering Analysis with Boundary Elements

    • ISSN: 0955-7997
    Aim of the JournalEngineering analysis with boundary elements is dedicated to the latest developments of engineering analysis with boundary elements, mesh reduction, and other related innovative and emerging numerical methods. The journal founded in 1984 was originally focused on the development of the Boundary Element Method. Its scope has since been expanded to include the emerging mesh reduction and meshless methods. The aim of the journal is to promote the use of non-traditional, innovative, and emerging computational methods for the analyses of modern engineering problems.ScopeEngine... Analysis with Boundary Elements publishes topics including: • Boundary Element Methods • Method of Fundamental Solutions and Related Methods • Radial Basis Function Collocation Methods • Other Mesh Reduction and Meshless Methods • Particle Methods • Other Emerging and Non-Traditional Numerical Methods • Advanced Engineering Analyses and Applications
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  • Historia Mathematica

    • ISSN: 0315-0860
    A publication of the International Commission on the History of Mathematics of the Division of the History of Science of the International Union of the History and Philosophy of Science.Historia Mathematica publishes historical scholarship on mathematics and its development in all cultures and time periods. In particular, the journal encourages informed studies on mathematicians and their work in historical context, on the histories of institutions and organizations supportive of the mathematical endeavor, on historiographical topics in the history of mathematics, and on the interrelations between mathematical ideas, science, and the broader culture.In addition to research articles, Historia Mathematica also publishes book reviews, abstracts of the current literature in the history of mathematics, notes and sources, and occasionally letters to the editor.Research Areas can include any of the following, provided that the article treats mathematics and its history in a substantial way:Historiography Interrelations between mathematics and the natural sciences, social sciences, humanities, arts, religion, and education Mathematicians and their work in context Organizations and institutions Pure and applied mathematical developments Sociology of mathematicsThis journal has an Open Archive. All published items, including research articles, have unrestricted access and will remain permanently free to read and download 48 months after publication. All papers in the Archive are subject to Elsevier's user license.
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  • Computational Statistics & Data Analysis

    • ISSN: 0167-9473
    The Official Journal of the Network Computational and Methodological Statistics (CMStatistics) and the International Association of Statistical Computing (IASC)Computational Statistics and Data Analysis (CSDA), an Official Publication of the network Computational and Methodological Statistics (CMStatistics) and of the International Association for Statistical Computing (IASC), is an international journal dedicated to the dissemination of methodological research and applications in the areas of computational statistics and data analysis. The journal consists of four refereed sections which are divided into the following subject areas:I) Computational Statistics - Manuscripts dealing with:the explicit impact of computers on statistical methodology (e.g., Bayesian computing, bioinformatics, computer graphics, computer intensive inferential methods, data exploration, data mining, expert systems, heuristics, knowledge based systems, machine learning, neural networks, numerical and optimization methods, parallel computing, statistical databases, statistical systems), the development, evaluation and validation of statistical software and algorithms. Software and algorithms can be submitted with manuscripts and will be stored together with the online article.II) Statistical Methodology for Data Analysis - Manuscripts dealing with: novel and original data analytical strategies and methodologies applied in biostatistics (design and analytic methods for clinical trials, epidemiological studies, statistical genetics, or genetic/environmenta... interactions), chemometrics, classification, data exploration, density estimation, design of experiments, environmetrics, education, image analysis, marketing, model free data exploration, pattern recognition, psychometrics, statistical physics, image processing, robust procedures. Statistical methodology includes, but not limited to: bootstrapping, classification techniques, clinical trials, data exploration, density estimation, design of experiments, pattern recognition/image analysis, parametric and nonparametric methods, statistical genetics, Bayesian modeling, outlier detection, robust procedures, cross-validation, functional data, fuzzy statistical analysis, mixture models, model selection and assessment, nonlinear models, partial least squares, latent variable models, structural equation models, supervised learning, signal extraction and filtering, time-series modelling, longitudinal analysis, multilevel analysis and quality control.III) Special Applications - Manuscripts at the interface of statistics and computing (e.g., comparison of statistical methodologies, computer-assisted instruction for statistics, simulation experiments). Advanced statistical analysis with real applications (social sciences, marketing, psychometrics, chemometrics, signal processing, medical statistics, environmentrics, statistical physics).IV) Statistical Data Science - The manuscripts concern with well-founded theoretical and applied data-driven research, with a significant computational or statistical methodological component for data analytics. Emphasis is given to comprehensive and reproducible research, including data-driven methodology, algorithms and software. This journal section serves as a complementary component to the network Computational and Methodological Statistics (CMStatistics).
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  • Journal of Approximation Theory

    • ISSN: 0021-9045
    The Journal of Approximation Theory is devoted to advances in pure and applied approximation theory and related areas. These areas include, among others:Classical approximation Abstract approximation Constructive approximation Degree of approximation Fourier expansions Interpolation of operatorsGeneral orthogonal systems Interpolation and quadratures Multivariate approximation Orthogonal polynomials Padé approximation Rational approximationSpline functions of one and several variables Approximation by radial basis functions in Euclidean spaces, on spheres, and on more general manifolds Special functions with strong connections to classical harmonic analysis, orthogonal polynomial, and approximation theory (as opposed to combinatorics, number theory, representation theory, generating functions, formal theory, and so forth) Approximation theoretic aspects of real or complex function theory, function theory, difference or differential equations, function spaces, or harmonic analysis Wavelet Theory and its applications in signal and image processing, and in differential equations with special emphasis on connections between wavelet theory and elements of approximation theory (such as approximation orders, Besov and Sobolev spaces, and so forth) Gabor (Weyl-Heisenberg) expansions and sampling theoryThis journal has an Open Archive. All published items, including research articles, have unrestricted access and will remain permanently free to read and download 48 months after publication. All papers in the Archive are subject to Elsevier's user license.
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  • Nonlinear Analysis: Real World Applications

    • ISSN: 1468-1218
    Nonlinear Analysis: Real World Applications welcomes all research articles of the highest quality with special emphasis on applying techniques of nonlinear analysis to model and to treat nonlinear phenomena with which nature confronts us. Coverage of applications includes any branch of science and technology such as solid and fluid mechanics, material science, mathematical biology and chemistry, control theory, and inverse problems.The aim of Nonlinear Analysis: Real World Applications is to publish articles which are predominantly devoted to employing methods and techniques from analysis, including partial differential equations, functional analysis, dynamical systems and evolution equations, calculus of variations, and bifurcations theory.Two papers per year rule All the authors and co-authors cannot submit more than two papers to this journal (including co-authored papers) within a period of twelve (12) months. If you or one of your co-authors have already submitted two papers within a period of 12 months or less, your third submission (if any) will be returned to you.Rejection due to poor English Some papers with good mathematics have been rejected from this journal due to the poor level of English within the paper. It is the responsibility of the author to ensure that the English language used is correct before submitting their paper. For authors whose first language is not English, we highly recommend that you have it checked by a native English speaker or make use of an English editing service. Elsevier also offers this (at a cost) via our Webshop (English Language Editing ).
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