Subject: Optimization methods and mathematical modeling (17.D0M39Z )
Native organizations units: No data
Study programmes of the course:
| Type of studies | Title |
|---|---|
| Doctoral Academic Studies | Mathematics in Engineering (Godina: 1, Winter) |
| Doctoral Academic Studies | Mathematics in Engineering (Godina: 2, Winter) |
Educational goal:
Enabling students to think abstractly and acquire knowledge in the field of selected optimization methods. The goal is to develop in the student the way of thinking that will enable postulating mathematical models for practical optimization problems and solve them successfully. These problems are of diverse nature, so the student is trained to use corresponding software for their solving (Matlab, Mathematica).
Educational outcome:
To utilize acquired knowledge in professional subjects and practical work, develop and solve mathematical models in the field of professional subjects using covered subject content in optimization methods.
Course content:
Theory (lectures): Mathematical modelling and simulation. Classic optimization methods. One-dimensional optimization. Convex and non-convex programming. Linear programming (graph method; simplex method, transport problem). Non linear programming (unconditional optimization, square programming, convex programming, separable programming, integer programming). Dynamic programming. Multicriteria optimization. Compromise programming. Abstract programming. Variation bill. Part of the teaching is realized through independent research and study work in the field of mathematics. Research and study work includes active following of primary scientific sources, organization and conducting experiments and statistical data processing, numeric simulation, possible writing of scientific paper in the field of mathematics.
Teaching methods:
Lectures. Consultations. Lectures are realized by combining theory and practice. Theoretical part is followed by appropriate examples which lead to clarification of the theoretical part. Apart from lectures and practical classes, consultations are held regularly. Part of subject content, which represents a logical unity, can be taken as a part of the exam during the teaching process. During lectures (through project work) it is necessary to prove elementary knowledge of at least one program packages (C, Pascal, Matlab. Mathematica) needed for modelling and simulation of a problem treated by optimization methods. Part of subject content as agreed upon and which makes unity is can be taken orally as a presentation and submitted in written form as a seminar paper. Oral part of the final exam is eliminatory. Through research and study work, student studies scientific journals and other relevant literature and individually expands subject content covered in classes. In cooperation with professor, student is enabled for independent writing of scientific paper.
Literature:
| Authors | Title | Year | Publisher | Language |
|---|---|---|---|---|
| Petrić, J. | Operaciona istraživanja | 1987 | Naučna knjiga, Beograd | Serbian language |
| Petrić, J., Zlobec, S. | Nelinearno programiranje | 1989 | Naučna knjiga, Beograd | Serbian language |
| 1985 | English | |||
| 1976 | English |
Knowledge evaluation:
| Course activity | Pre-examination | Obligations | Number of points |
|---|---|---|---|
| Theoretical part of the exam | No | Yes | 55.00 |
| Term paper | Yes | Yes | 20.00 |
| Project defence | Yes | Yes | 20.00 |
| Lecture attendance | Yes | Yes | 5.00 |
Lecturers:
prof. dr Ralević Nebojša
Full Professor
Study research work
doc. dr Ovcin Zoran
Assistant Professor
Study research work
prof. dr Ralević Nebojša
Full Professor
Lectures
doc. dr Ovcin Zoran
Assistant Professor
Lectures
prof. dr Lukić Tibor
Full Professor
Lectures
prof. dr Lukić Tibor
Full Professor
Study research work
Faculty of Technical Sciences
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Contact:
Address: Trg Dositeja Obradovića 6, 21102 Novi Sad
© 2024. Faculty of Technical Sciences.