Nonlinear Optimization
Some basic information about the module
The aim of studying and bibliography
The main aim of study:
Preparing students to use algorithms and non-linear programming techniques to solve optimization problems
The general information about the module:
The module is implemented in the fifth semester (15 hours of lectures, 15 hours of laboratory classes and 15 hours of project classes)
Bibliography required to complete the module
| 1 | J.G. Ecker, M. Kupferschmid | Introduction to Operations Research | John Wiley & Sons, New York. | 1988 |
| 2 | W. Findeisen, J. Szymanowski, A. Wierzbicki | Teoria i metody obliczeniowe optymalizacji | PWN, Warszawa. | 1980 |
| 1 | H. Wickham | Język R: kompletny zestaw narzędzi dla analityków danych | Wydawnictwo Helion, Gliwice . | 2018 |
| 2 | P. Biecek | Przewodnik po pakiecie R | GiS, Wrocław . | 2017 |
| 1 | K. Kukuła (red.) | Badania operacyjne w przykładach i zadaniach | PWN, Warszawa. | 2016 |
Basic requirements in category knowledge/skills/social competences
Formal requirements:
The fifth semester of a degree in engineering and data analysis. The student satisfies the formal requirements set out in the study regulations.
Basic requirements in category knowledge:
Knowledge of basic concepts of linear algebra and mathematical analysis
Basic requirements in category skills:
Ability to perform operations on matrices and vectors, solving systems of linear equations, calculating derivatives and integrals. Knowledge of the basics of programming in R
Basic requirements in category social competences:
Willingness to continue to acquire mathematical knowledge. Ability to work in a group
Module outcomes
| MEK | The student who completed the module | Types of classes / teaching methods leading to achieving a given outcome of teaching | Methods of verifying every mentioned outcome of teaching | Relationships with KEK | Relationships with PRK |
|---|---|---|---|---|---|
| MEK01 | understands the basic concepts of non-linear programming, knows optimality conditions and can determine the minimum and maximum of a function of one and many variables (without constraints) | lectures, laboratory and project classes | written test, project evaluation |
K-W02+ K-W03++ K-U03++ K-U24+ K-K02+ |
P6S-KK P6S-KO P6S-UK P6S-UO P6S-UW P6S-WG |
| MEK02 | knows how to use the Lagrange multipliers method and how to identify inactive constraints, knows the selected properties of convex functions and the basics of the Karush-Kun-Tucker theory | lectures, laboratory and project classes | written test, project evaluation |
K-W02+ K-W03++ K-U03++ K-U24+ K-K02+ |
P6S-KK P6S-KO P6S-UK P6S-UO P6S-UW P6S-WG |
| MEK03 | knows selected numerical methods of nonlinear optimization and can apply them in simple situations using the R Program | laboratory and project classes | project evaluation |
K-W02+ K-U03+++ K-U08+ K-U25+ K-K04++ |
P6S-KO P6S-KR P6S-UU P6S-UW P6S-WG |
The syllabus of the module
| Sem. | TK | The content | realized in | MEK |
|---|---|---|---|---|
| 5 | TK01 | W1-W2, L1-L4 | MEK01 MEK03 | |
| 5 | TK02 | W3-W8, L5-L8 | MEK01 MEK03 | |
| 5 | TK03 | W9-W15, L9-L15 | MEK02 MEK03 | |
| 5 | TK04 | L1-L15, P1-P10 | MEK01 MEK02 MEK03 | |
| 5 | TK05 | P11-P15 | MEK03 |
The student's effort
| The type of classes | The work before classes | The participation in classes | The work after classes |
|---|---|---|---|
| Lecture (sem. 5) | contact hours:
15.00 hours/sem. |
||
| Laboratory (sem. 5) | contact hours:
15.00 hours/sem. |
Finishing/Making the report:
4.00 hours/sem. |
|
| Project/Seminar (sem. 5) | The preparation for projects/seminars:
3.00 hours/sem. |
contact hours:
15.00 hours/sem.. |
Doing the project/report/ Keeping records:
5.00 hours/sem. The preparation for the presentation: 1.00 hours/sem. Others: 1.00 hours/sem. |
| Advice (sem. 5) | The participation in Advice:
1.00 hours/sem. |
||
| Credit (sem. 5) |
The way of giving the component module grades and the final grade
| The type of classes | The way of giving the final grade |
|---|---|
| Lecture | Pass of the lecture is based on a positive assessment of all projects |
| Laboratory | Pass of the laboratory is based on a positive assessment of all projects |
| Project/Seminar | Pass of the project classes is based on a positive assessment of all projects |
| The final grade |
Sample problems
Required during the exam/when receiving the credit
(-)
Realized during classes/laboratories/projects
OL.pdf
Others
(-)
Can a student use any teaching aids during the exam/when receiving the credit : no