Type of studies | Title |
---|---|
Master Academic Studies | Information and Analytics Engineering (Year: 1, Semester: Summer) |
Master Academic Studies | Mathematics in Engineering (Year: 1, Semester: Summer) |
Master Academic Studies | Information Engineering (Year: 1, Semester: Summer) |
Category | Theoretical-methodological |
Scientific or art field | Teorijska i primenjena matematika |
ECTS | 5 |
Enabling students to develop abstract thinking and acquire knowledge about the theory of nonlinear programming. The goals of the course are to develop a way of thinking in the students, that will enable constructing a mathematical model for the optimization problems stemming from applications, and to successfully solve such models. The majority of the problems are expected to be non-linear and of diverse nature. Thus, to successfully solve them, the student is trained to use the appropriate software (matlab, Mathematica).
To use the acquired knowledge in further education and in practice, postulate and solve mathematical models in engineering subjects using the knowledge about nonlinear programming. The models usually originate from applications and multidisciplinary knowledge is required for solving them successfully.
Theoretical teaching (lectures): Introduction (convex sets, convex functions). Classic optimization methods (method of elimination of variables, Lagrange multiplier method, Courant method). One-dimensional optimization (Fibonacci method, golden section method; Newton's method; cut-method; polynomial approximation method). Unconditional optimization without calculation of derivatives (Hooke-Jeeves's method; Powell's method) unconditional optimization for differential functions (Cauchy's method of the sharpest decay; modification of Cauchy's method; Newton's method; methods of variable metric). Convex programming (convex programs, Kuhn-Tucker theorems, linear constrained programs, dual problems). Practical classes (exercises): The exercises work on appropriate examples from theoretical instruction that trains the given material and, therefore, the exercises contribute to the understanding of the given material.
Lectures. Numerical calculation classes. Consultations. Lectures are organized in combined form. The presentation of the theoretical part is followed by the corresponding examples which contribute to better understanding of the theoretical part. During the practice classes which follow the lectures, the subject matter is supported by characteristic examples to provide further practice and better understanding In addition to lectures and practice classes there are regular consultations. The students can take partial exams during the course.
Authors | Title | Year | Publisher | Language |
---|---|---|---|---|
2006 | English | |||
1979 | English |
Course activity | Pre-examination | Obligations | Number of points |
---|---|---|---|
Test | Yes | Yes | 10.00 |
Final exam - part one | No | No | 25.00 |
Lecture attendance | Yes | Yes | 3.00 |
Project | Yes | Yes | 15.00 |
Test | Yes | Yes | 10.00 |
Exercise attendance | Yes | Yes | 2.00 |
Test | Yes | Yes | 10.00 |
Final exam - part two | No | No | 25.00 |
Written part of the exam - tasks and theory | No | Yes | 50.00 |
Full Professor
Assistant Professor
Assistant Professor
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© 2024. Faculty of Technical Sciences.