Faculty of Technical Sciences

Subject: Nonlinear programming and evolutionary algorithms (17.SEAU01)

Native organizations units: Sub-department for Automatic Control and Systems Engineering
General information:
 
Category Theoretical-methodological
Scientific or art field Automatic Control and System Engineering
ECTS 4

The main objective of the course is to acquire knowledge on the types of nonlinear optimization methods and evolutionary programming techniques.

The acquired knowledge can be used in solving practical engineering problems and forms a basis for future engineering subjects.

Basic principles of optimization. Optimization problem. One-dimensional optimization. Sufficient and necessary conditions in the scalar case. One-dimensional search algorithms. Multidimensional search optimization without constraints. Bounded variation method. Lagrange multipliers method. Multidimensional numerical optimization. Newton and quasi-Newton algorithms. Nealder-Meade algorithms. Multidimensional constrained optimization methods. Basic principles of convex programming. Kuhn-Tucker conditions. Numerical methods of multidimensional constrained programming. Linear programming. Quadratic programming. Basic principles of global optimization. Evolutionarz and genetic computation. Particle swarm optimization. Basic principles of modern global optimization algorithms: ACO (Ant Colony Optimization), BFO (Bacteria Foragging Optimization), ...

Lectures. Study. Research

Authors Title Year Publisher Language
Course activity Pre-examination Obligations Number of points
Test Yes Yes 10.00
Test Yes Yes 10.00
Written part of the exam - tasks and theory No Yes 50.00
Homework Yes Yes 30.00
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Prof. Rapaić Milan

Full Professor

Lectures
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Prof. Jeličić Zoran

Full Professor

Lectures
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Assoc. Prof. Radović Mirna

Associate Professor

Lectures

Assistant - Master Golić Anastasija

Assistant - Master

Practical classes
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Assoc. Prof. Radović Mirna

Associate Professor

Computational classes

Assistant - Master Golić Anastasija

Assistant - Master

Computational classes

Faculty of Technical Sciences

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(+381) 21 6350 413

Fax : (+381) 21 458 133
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© 2024. Faculty of Technical Sciences.