Numerical Optimization: Algorithms and Applications
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E: Applied Mathematics".
Deadline for manuscript submissions: 30 September 2025 | Viewed by 109
Special Issue Editor
2. Department of Mathematics and Statistics, Curtin University, Perth, WA 6845, Australia
Interests: nonlinear analysis on manifolds; optimization for process modeling; simulation and applications; fractional order differential equations; partial differential equation; critical points theory; nonlinear systems; fractional calculus; mathematical modeling
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Optimization has a wide range of uses in science, engineering, economics, and industry. The practice of optimization depends not only on efficient and robust algorithms but also on good modeling techniques, careful interpretation of results and user-friendly software.
The development and improvement of optimization techniques are of great significance for the study of corresponding science problems. The aim of this Special Issue is to report on the latest achievements and recent development in the algorithms and applications for optimization problems, including in largescale optimization techniques such as interior-point methods, inexact Newton methods, limited-memory methods and some numerical optimizations that are not limited.
This Special Issue will collect high-quality original research articles as well as review articles in the above scope.
Dr. Xinguang Zhang
Guest Editor
Manuscript Submission Information
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Keywords
- optimization for process modeling
- numerical simulation of the optimization problems
- optimization for process control
- global optimization
- stochastic optimization
- robust optimization
- multi-criteria optimization problems
- operations research problems
- optimization on graphs and networks
- optimization in logistics
- optimization of manufacturing processes
- vehicle routing and other transportation problems
- control-theoretic problems
- exact solution algorithms
- machine-learning
- complexity issues
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