Administracja Centralna Uczelni - Wymiana międzynarodowa (S2)
Sylabus przedmiotu Optimization Theory:
Informacje podstawowe
| Kierunek studiów | Wymiana międzynarodowa | ||
|---|---|---|---|
| Forma studiów | studia stacjonarne | Poziom | drugiego stopnia |
| Tytuł zawodowy absolwenta | |||
| Obszary studiów | — | ||
| Profil | |||
| Moduł | — | ||
| Przedmiot | Optimization Theory | ||
| Specjalność | przedmiot wspólny | ||
| Jednostka prowadząca | Katedra Elektrotechniki Teoretycznej i Informatyki | ||
| Nauczyciel odpowiedzialny | Marcin Ziółkowski <Marcin.Ziolkowski@zut.edu.pl> | ||
| Inni nauczyciele | |||
| ECTS (planowane) | 5,0 | ECTS (formy) | 5,0 |
| Forma zaliczenia | zaliczenie | Język | angielski |
| Blok obieralny | — | Grupa obieralna | — |
Formy dydaktyczne
Wymagania wstępne
| KOD | Wymaganie wstępne |
|---|---|
| W-1 | Numerical Methods, Mathematics, Physics |
Cele przedmiotu
| KOD | Cel modułu/przedmiotu |
|---|---|
| C-1 | Students will get the knowledge about various optimization methods. They will be able to use an appropriate method to the given practical problem. |
Treści programowe z podziałem na formy zajęć
| KOD | Treść programowa | Godziny |
|---|---|---|
| laboratoria | ||
| T-L-1 | One-Dimensional Search Methods (Golden Section Search, Fibonacci Search, Newton's Method, Secant Method) | 3 |
| T-L-2 | Gradient Methods | 3 |
| T-L-3 | Genetic Algorithms | 3 |
| T-L-4 | Simplex Methods, Non-Simplex Methods | 3 |
| T-L-5 | Single Objective Optimization and Multi Objective Optimization Problems | 3 |
| T-L-6 | Single Objective Optimization of an Exciter for Magnetic Induction Tomography | 3 |
| T-L-7 | Multi Objective Optimization of an Exciter for Magnetic Induction Tomography | 3 |
| T-L-8 | Magnetic Field Synthesis on a Solenoid's Axis | 3 |
| T-L-9 | Solving Ax = b using Least-Squares Analysis, Recursive Least-Squares Algorithm, Solution to Ax = b Minimizing ||x||) | 3 |
| T-L-10 | Topology Optimization of a Magnetic Field in a Three-dimensional Finite Region | 3 |
| 30 | ||
| wykłady | ||
| T-W-1 | One-Dimensional Search Methods (Golden Section Search, Fibonacci Search, Newton's Method, Secant Method) | 4 |
| T-W-2 | Gradient Methods | 4 |
| T-W-3 | Genetic Algorithms | 2 |
| T-W-4 | Simplex Methods, Non-Simplex Methods | 2 |
| T-W-5 | Single Objective Optimization of an Exciter for Magnetic Induction Tomography | 4 |
| T-W-6 | Multi Objective Optimization of an Exciter for Magnetic Induction Tomography | 4 |
| T-W-7 | Magnetic Field Synthesis on a Solenoid's Axis | 4 |
| T-W-8 | Solving Ax = b using Least-Squares Analysis, Recursive Least-Squares Algorithm, Solution to Ax = b Minimizing ||x||) | 2 |
| T-W-9 | Topology Optimization of a Magnetic Field in a Three-dimensional Finite Region | 4 |
| 30 | ||
Obciążenie pracą studenta - formy aktywności
| KOD | Forma aktywności | Godziny |
|---|---|---|
| laboratoria | ||
| A-L-1 | uczestnictwo w zajęciach | 30 |
| A-L-2 | Przygotowanie do zajęć | 30 |
| 60 | ||
| wykłady | ||
| A-W-1 | uczestnictwo w zajęciach | 30 |
| A-W-2 | Praca własna | 60 |
| 90 | ||
Metody nauczania / narzędzia dydaktyczne
| KOD | Metoda nauczania / narzędzie dydaktyczne |
|---|---|
| M-1 | Tradycyjny wykład + laboratorium komputerowe |
Sposoby oceny
| KOD | Sposób oceny |
|---|---|
| S-1 | Ocena formująca: Ocenianie podczas zajęć |
Zamierzone efekty uczenia się - wiedza
| Zamierzone efekty uczenia się | Odniesienie do efektów kształcenia dla kierunku studiów | Odniesienie do efektów zdefiniowanych dla obszaru kształcenia | Cel przedmiotu | Treści programowe | Metody nauczania | Sposób oceny |
|---|---|---|---|---|---|---|
| WM-WE_2-_??_W01 Students will get the knowledge about various optimization methods. They will be able to use an appropriate method to the given practical problem. | — | — | C-1 | T-W-5, T-W-9, T-W-8, T-W-2, T-W-4, T-W-3, T-W-6, T-W-1, T-W-7 | M-1 | S-1 |
Zamierzone efekty uczenia się - umiejętności
| Zamierzone efekty uczenia się | Odniesienie do efektów kształcenia dla kierunku studiów | Odniesienie do efektów zdefiniowanych dla obszaru kształcenia | Cel przedmiotu | Treści programowe | Metody nauczania | Sposób oceny |
|---|---|---|---|---|---|---|
| WM-WE_2-_??_U01 Students will get the knowledge about various optimization methods. They will be able to use an appropriate method to the given practical problem. | — | — | C-1 | T-L-2, T-L-10, T-L-6, T-L-7, T-L-1, T-L-8, T-L-5, T-L-3, T-L-9, T-L-4 | M-1 | S-1 |
Zamierzone efekty uczenia się - inne kompetencje społeczne i personalne
| Zamierzone efekty uczenia się | Odniesienie do efektów kształcenia dla kierunku studiów | Odniesienie do efektów zdefiniowanych dla obszaru kształcenia | Cel przedmiotu | Treści programowe | Metody nauczania | Sposób oceny |
|---|---|---|---|---|---|---|
| WM-WE_2-_??_K01 Students will get the knowledge about various optimization methods. They will be able to use an appropriate method to the given practical problem. | — | — | C-1 | T-L-1, T-L-7, T-L-5, T-W-4, T-L-2, T-W-6, T-W-7, T-L-8, T-L-9, T-W-8, T-W-5, T-L-3, T-W-9, T-L-10, T-W-2, T-L-6, T-W-1, T-W-3, T-L-4 | M-1 | S-1 |
Kryterium oceny - wiedza
| Efekt uczenia się | Ocena | Kryterium oceny |
|---|---|---|
| WM-WE_2-_??_W01 Students will get the knowledge about various optimization methods. They will be able to use an appropriate method to the given practical problem. | 2,0 | The student received a score of less than 50% of the credit questions. |
| 3,0 | The student received points in the range of 50-60% of credit questions. | |
| 3,5 | The student received points in the range of 61-70% of the credit questions. | |
| 4,0 | The student received a score in the range of 71-80% of the credit questions. | |
| 4,5 | The student obtained points in the range of 81-90% of the credit questions. | |
| 5,0 | The student obtained points in the range of 91-100% of the credit questions. |
Kryterium oceny - umiejętności
| Efekt uczenia się | Ocena | Kryterium oceny |
|---|---|---|
| WM-WE_2-_??_U01 Students will get the knowledge about various optimization methods. They will be able to use an appropriate method to the given practical problem. | 2,0 | The student received a score of less than 50% of the credit questions. |
| 3,0 | The student received points in the range of 50-60% of credit questions. | |
| 3,5 | The student received points in the range of 61-70% of the credit questions. | |
| 4,0 | The student received a score in the range of 71-80% of the credit questions. | |
| 4,5 | The student obtained points in the range of 81-90% of the credit questions. | |
| 5,0 | The student obtained points in the range of 91-100% of the credit questions. |
Kryterium oceny - inne kompetencje społeczne i personalne
| Efekt uczenia się | Ocena | Kryterium oceny |
|---|---|---|
| WM-WE_2-_??_K01 Students will get the knowledge about various optimization methods. They will be able to use an appropriate method to the given practical problem. | 2,0 | The student received a score of less than 50% of the credit questions. |
| 3,0 | The student received points in the range of 50-60% of credit questions. | |
| 3,5 | The student received points in the range of 61-70% of the credit questions. | |
| 4,0 | The student received a score in the range of 71-80% of the credit questions. | |
| 4,5 | The student obtained points in the range of 81-90% of the credit questions. | |
| 5,0 | The student obtained points in the range of 91-100% of the credit questions. |
Literatura podstawowa
- Edwin K.P. Chong, Stanislaw H. Żak, An Introduction to Optimization, Wiley & Sons, New York, USA, 2001