Deadline Date: 31 March 2027
Industrial mathematics concerns the analysis and solution of problems that arise in industries, corporations, government agencies, and other organizational settings. Its purpose is to produce optimal, efficient, and reliable solutions to support decision-making and innovation in finance, environmental sustainability, production systems, resource management, and technology development. As modern industry becomes more complex and sophisticated, there is a growing need for professionals who can understand technical challenges, formulate accurate mathematical models, implement solutions through advanced computational and digital techniques, and communicate these solutions effectively to engineers, workers, managers, and decision makers.
Industrial mathematics is an interdisciplinary area of applied mathematics concerned with complicated problems emerging in industrial engineering and related subjects. It utilizes a wide variety of analytical, computational, and numerical methods, including integral and differential equations, interpolation, polynomial computation, least-squares methods, regularization, vector and matrix algebra, control, synthesis, discrete and continuous transforms, image and signal processing, Galerkin methods, finite-element methods, spectral methods, shooting methods, finite-difference methods, and finite-volume methods. Industrial mathematics combines the power of mathematics, statistics, optimization, engineering, computer science, and business-oriented techniques for modeling, analysis, simulation, and decision-making. These interdisciplinary abilities are becoming increasingly essential in academia, research institutes, and industry, especially as modern technology problems require efficient and mathematically precise solutions.
This Special Issue aims to promote research and applications of industrial mathematics, with a focus on industrial and/or real-world applications of mathematical concepts.
Topics of interest include, but are not limited to, the following:
Operations research and its industrial applications
Statistical methods, modeling, and data analysis
Reliability engineering and risk assessment
Optimization models, algorithms, and methods
Industrial applications of computing and artificial intelligence
Successful case studies demonstrating the role of industrial mathematics
Applied mathematical methods in management, science, and engineering
Mathematical modeling and simulation in fluid mechanics
Editorial board
