Numerical Optimization: Mathematical Problems and Applications
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Computational and Applied Mathematics".
Deadline for manuscript submissions: closed (31 July 2020) | Viewed by 2008
Special Issue Editor
Interests: Applied Mathematics; Mathematical Physics; MATLAB Simulation; FPGA Accelerators; Nonlinear Dynamics; Advanced Control Theory; Fractional Calculus; Embedded Systems; Artificial Intelligence; Machine learning; System Modeling; Electrical & Electronics Engineering; Automation & Robotics; Human-Machine Interfaces; Mechatronics; Control and Instrumentation; Power Systems Modelling
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Special Issue Information
Dear Colleagues,
Almost every problem in science and technology can be formulated as an optimization problem. When solving these problems, computational methods based on mathematical analysis and natural calculations are used. At the same time, in practice, the problems of approximate solutions to optimization problems, the analysis of computational errors, and the convergence of computational methods come to the fore. In a number of complex problems, it is very difficult or impossible to obtain an analytical solution by means of mathematical analysis; therefore the issues of numerical algorithms are equally important. The purpose of this Special Issue is to establish a collection of articles that reflect the latest mathematical developments in the field of numerical optimization with their applications. The topics of this Special Issue include, but are not limited to:
- Inverse and Incorrect Problems of Control Theory
- Problems of Perturbation of the Spectrum of Operators in the Theory of Dynamical Systems
- Simulation-based optimization
- Nonlinear ODEs and PDEs
- Applied Mathematical Modelling in Fluid and Solid Mechanics
- Analytical Approximate Methods
- Fractional Calculus
Dr. Anton Zhilenkov
Guest Editor
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Keywords
- Inverse and ill-posed problems
- Perturbation of the spectrum of operators
- Predictor–corrector method
- Simulation-based optimization
- Numerical algorithms
- Convergence analysis
- Nonsmooth optimization
- Near-optimal solution
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