Journals in Numerical methods in engineering

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, R. Roet-Green, 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: 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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Probabilistic Engineering Mechanics

ISSN: 0266-8920

This journal provides a forum for scholarly work dealing primarily with probabilistic and statistical approaches to contemporary solid/structural and fluid mechanics problems encountered in diverse technical disciplines such as aerospace, civil, marine, mechanical, and nuclear engineering. The journal aims to maintain a healthy balance between general solution techniques and problem-specific results, encouraging a fruitful exchange of ideas among disparate engineering specialities.From time to time, review papers will be published to provide research and development oriented readers with state-of-the-art analyses of various areas of current interest. In addition, occasional papers of tutorial nature help enhance practice oriented readers' knowledge of the basic probabilistic and statistical techniques that are essential in present-day engineering practice design.In consultation with the editors, distinguished members of the probabilistic mechanics community may serve as guest editors for a special issue dedicated to a particular theme.Fields Covered:Aerospace engineering: • Damage-tolerant and durability design of aircraft • Load spectra characterisation • Random vibration of aerospace structuresCivil engineering: • Geotechnical applications • Natural hazards such as earthquakes, hurricanes, and waves • Stochastic fluid mechanics/hydrology • Structural response/control under natural hazardsMarine engineering: • Offshore structures response to wind-induced waves • Ship motion in a random seaMechanical engineering: • Fatigue design • Mechanical systems response/control • Vehicle vibration • Vibration isolationNuclear engineering: • Probabilistic risk assessment • Structural and equipment response to accidental loadsCommon to all disciplines: • Composite materials • Damage mechanics • Monte Carlo simulation • Random fields • Stochastic finite elements • Stochastic optimization • System reliability.

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Reliability Engineering & System Safety

ISSN: 0951-8320

Published by Elsevier in association with the European Safety and Reliability Association, and the Safety Engineering and Risk Analysis DivisionReliability Engineering and System Safety is an international journal devoted to the development and application of methods for the enhancement of the safety and reliability of complex technological systems, like nuclear power plants, chemical plants, hazardous waste facilities, space systems, offshore and maritime systems, transportation systems, constructed infrastructure and manufacturing plants. The journal normally publishes only articles that involve the analysis of substantive problems related to the reliability of complex systems or present techniques and/or theoretical results that have a discernable relationship to the solution of such problems. An important aim is to achieve a balance between academic material and practical applications.The following topics are within the scope of the journal: methods for reliability and probabilistic safety assessment; model and parameter uncertainties; aleatory and epistemic uncertainties, sensitivity analysis, data collection and analysis; engineering judgement and expert opinions; human reliability; test and maintenance policies; models for ageing and life extension; systems analysis of the impact of earthquakes, fires, tornadoes, winds, floods, etc.; codes, standards and safety criteria; operator decision support systems; software reliability; methods and applications of automatic fault detection and diagnosis; dynamic reliability; design and evaluation of man machine systems and human interfaces; design innovation for safety and reliability; safety culture; accident investigation and management. The journal does not normally publish articles that involve fuzzy sets and related non-probabilistic methods unless they contribute significantly to the solution of substantive problems related to the analysis of real systems.The journal will contain contributed material in the form of original research papers, review articles, industrial case studies, safety recommendations, and short communications.

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Soil Dynamics and Earthquake Engineering

ISSN: 0267-7261

The journal aims to encourage and enhance the role of mechanics and other disciplines as they relate to earthquake engineering by providing opportunities for the publication of the work of applied mathematicians, engineers and other applied scientists involved in solving problems closely related to the field of earthquake engineering and geotechnical earthquake engineering.Emphasis is placed on new concepts and techniques and case histories are considered only if they enhance the presentation and understanding on new technical concepts associated with analysis.Fields Covered:Seismology and Geology relevant to earthquake engineering problems with emphasis on modeling and methodologies and consideration of their effects on the analysis and design of structures.Wave propagation, wave scattering and dynamic crack propagation in soils and rocks under elastic or inelastic material behavior.Dynamic constitutive behavior of materials.Dynamic interaction problems (soil-structure interaction, fluid-structure interaction and tsunamis if only related to its geotechnical and structural systems).Seismic analysis and design of steel and reinforced concrete structures, retaining walls, dams, slopes.Effect of moving loads on bridges and pavements and vibration isolation in geotechnical structures.Inverse problems, identification and structural health monitoring in earthquake engineering.Instrume... and experimental methods in earthquake engineering.Applied mathematical methods and artificial intelligence for earthquake engineering analysis and design.Performance-b... seismic design of structures.Probabili... methods in earthquake engineering including risk analysis and reliability Earthquake case histories and lessons learned from catastrophic ground motions.Earthquake case histories and lessons learned from catastrophic ground motions only if they include modeling and geotechnical/structu... analysis.

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Structural Safety

ISSN: 0167-4730

An International Journal on Integrated Risk Assessment for Constructed FacilitiesStructural Safety is an international journal devoted to integrated risk assessment for a wide range of constructed facilities such as buildings, bridges, earth structures, offshore facilities, dams, lifelines and nuclear structural systems. Its purpose is to foster communication about risk and reliability among technical disciplines involved in design and construction, and to enhance the use of risk management in the constructed environment. All aspects of quantitative safety assessment are of interest:• Loads and environmental effects; • Material properties; • Prediction of response and performance; • Treatment of human error and engineering judgment; • Quality assurance/control; and • Techniques of decision analysis and risk management.Benefits to authors We also provide many author benefits, such as free PDFs, a liberal copyright policy, special discounts on Elsevier publications and much more. Please click here for more information on our author services.Please see our Guide for Authors for information on article submission. If you require any further information or help, please visit our Support Center

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Journals in Numerical methods in engineering

Operations Research Letters

Probabilistic Engineering Mechanics

Reliability Engineering & System Safety

Soil Dynamics and Earthquake Engineering

Structural Safety

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