Faculty of Technical Sciences

Subject: Nonlinear programming (17.0M527)

Native organizations units: Department of Fundamentals Sciences
General information:
 
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
Nocedal, J., Wright, S. Numerical Optimization 2006 Springer, New York English
Bazaraa, M.S., Shetty, C.M. Nonlinear programming : theory and algorithms 1979 John Wiley and Sons, New York 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

Prof. Ralević Nebojša

Full Professor

Lectures
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Asst. Prof. Duraković Nataša

Assistant Professor

Practical classes
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Asst. Prof. Delić Marija

Assistant Professor

Computational classes

Faculty of Technical Sciences

© 2024. Faculty of Technical Sciences.

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(+381) 21 6350 413

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© 2024. Faculty of Technical Sciences.