Mathematical Modeling and Numerical Optimization with Its Applications
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E: Applied Mathematics".
Deadline for manuscript submissions: 31 January 2027 | Viewed by 1477
Special Issue Editor
Special Issue Information
Dear Colleagues,
Mathematical models, as part of the scientific method, are mathematical pictures of reality and represent a description of an object or system by applying particular mathematical concepts and symbols. They are often expressed in terms of ordinary differential equations and partial differential equations. Mathematical models can also be statistical models, fuzzy logic models, and empirical relationships. In fact, any model description using mathematical language can be called a mathematical model. On the other hand, numerical optimization, also called mathematical programming, is an area of applied mathematics that allows for finding “the best” alternative for a given situation through the systematic analysis of the possible alternatives of the situation at hand.
Good mathematical models and the proper use of classical and modern mathematical theory, as well as current numerical optimization techniques, are of vital importance to improve reliability and precision in the management of practical applications in real life.
We are pleased to invite you to submit original research articles and reviews where mathematical modeling or numerical optimization techniques are used to solve any type of real-life problem in the fields of engineering and natural, medical, or social sciences, among others. Please feel free to share this invitation with your colleagues.
If you have any questions regarding this Special Issue, please do not hesitate to contact us. We look forward to receiving your contributions.
Prof. Dr. Héctor Jairo Martínez-Romero
Guest Editor
Manuscript Submission Information
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Keywords
- mathematical modeling
- numerical optimization
- artificial neural network
- operations research
- genetic algorithm
- linear and nonlinear programming
- integer programming
- complementary problem
- complex networks
- experimental data
- mathematical epidemiology
- optimal control
- biological control
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