Administracja Centralna Uczelni - Wymiana międzynarodowa (S2)
Sylabus przedmiotu Fundamentals of optimization techniques in engineering:
Informacje podstawowe
| Kierunek studiów | Wymiana międzynarodowa | ||
|---|---|---|---|
| Forma studiów | studia stacjonarne | Poziom | drugiego stopnia |
| Tytuł zawodowy absolwenta | |||
| Obszary studiów | — | ||
| Profil | |||
| Moduł | — | ||
| Przedmiot | Fundamentals of optimization techniques in engineering | ||
| Specjalność | przedmiot wspólny | ||
| Jednostka prowadząca | Instytut Inżynierii Chemicznej i Procesów Ochrony Środowiska | ||
| Nauczyciel odpowiedzialny | Halina Murasiewicz <Halina.Murasiewicz@zut.edu.pl> | ||
| Inni nauczyciele | Bogdan Ambrożek <Bogdan.Ambrozek@zut.edu.pl> | ||
| ECTS (planowane) | 4,0 | ECTS (formy) | 4,0 |
| Forma zaliczenia | zaliczenie | Język | polski |
| Blok obieralny | — | Grupa obieralna | — |
Formy dydaktyczne
Wymagania wstępne
| KOD | Wymaganie wstępne |
|---|---|
| W-1 | Chemical engineering fundamentals |
| W-2 | Applied Mathematics |
Cele przedmiotu
| KOD | Cel modułu/przedmiotu |
|---|---|
| C-1 | Student after successful completion of course is excepted to have: • Knowledge of basic optimization techniques. • Ability to formulate decision problems as optimization problems. • Ability to solve simple problems, select appropriate method and to use the right software to solve complicated problems. |
Treści programowe z podziałem na formy zajęć
| KOD | Treść programowa | Godziny |
|---|---|---|
| ćwiczenia audytoryjne | ||
| T-A-1 | Students will solve individual problems during the classes. The typical probles are similar to these: Golden-section search | 5 |
| T-A-2 | Newton's Method. Grid search method | 5 |
| T-A-3 | Relaxation (approximation) | 5 |
| T-A-4 | Gradients method | 5 |
| T-A-5 | Lagrange multiplier methods | 5 |
| T-A-6 | Simplex Method | 5 |
| 30 | ||
| wykłady | ||
| T-W-1 | Introduction to the optimization problems. Fundamental definitions: goal function, optimization variables, requirements and conditions of the unique optimal solution | 2 |
| T-W-2 | Fundamentals of mathematical modelling | 2 |
| T-W-3 | Fundamentals of the non-gradient optimization methods | 2 |
| T-W-4 | Unconstrained Optimization - introduction, definition and examples | 2 |
| T-W-5 | Direct search methods: golden section and Fibonacci techniques, Newton’s method | 2 |
| T-W-6 | Discrete Optimization problems | 2 |
| T-W-7 | Introduction to genetic algorithms | 2 |
| T-W-8 | Optimization methods for constrained optimization problems: Lagrange and penalty function methods | 4 |
| T-W-9 | Optimization methods: Pareto compromise approach. | 2 |
| T-W-10 | Fundamentals of the linear programming: graphic method. | 2 |
| T-W-11 | Simplex method for linear optimization problems. | 2 |
| T-W-12 | Fundamentals of dynamic optimization | 2 |
| T-W-13 | Fundamentals of robust optimization:Local robustness, Global robustness, Stability radius | 4 |
| 30 | ||
Obciążenie pracą studenta - formy aktywności
| KOD | Forma aktywności | Godziny |
|---|---|---|
| ćwiczenia audytoryjne | ||
| A-A-1 | Class participation | 30 |
| A-A-2 | One-on-One Teaching Consultations | 30 |
| 60 | ||
| wykłady | ||
| A-W-1 | Class participation | 30 |
| A-W-2 | One-on-One Teaching Consultations | 30 |
| 60 | ||
Metody nauczania / narzędzia dydaktyczne
| KOD | Metoda nauczania / narzędzie dydaktyczne |
|---|---|
| M-1 | activating methods: lecture and didactic discussion |
| M-2 | practical methods - tutorials |
Sposoby oceny
| KOD | Sposób oceny |
|---|---|
| S-1 | Ocena formująca: assessment of progress of the work - monthly |
| S-2 | Ocena podsumowująca: written final report/test |
Zamierzone efekty kształcenia - wiedza
| Zamierzone efekty kształcenia | Odniesienie do efektów kształcenia dla kierunku studiów | Odniesienie do efektów zdefiniowanych dla obszaru kształcenia | Cel przedmiotu | Treści programowe | Metody nauczania | Sposób oceny |
|---|---|---|---|---|---|---|
| WM-WTiICh_2-_null_W01 Student has theoretical knowledge of the theory and methods of optimization which allows the analysis and modeling of data and processes | — | — | C-1 | T-W-8, T-W-4, T-W-9, T-W-3, T-W-6, T-W-12, T-W-5, T-W-10, T-W-13, T-W-1, T-W-2, T-W-7, T-W-11 | M-1 | S-2, S-1 |
Zamierzone efekty kształcenia - umiejętności
| Zamierzone efekty kształcenia | Odniesienie do efektów kształcenia dla kierunku studiów | Odniesienie do efektów zdefiniowanych dla obszaru kształcenia | Cel przedmiotu | Treści programowe | Metody nauczania | Sposób oceny |
|---|---|---|---|---|---|---|
| WM-WTiICh_2-_null_U01 Student knows chosen methods and software tools for deterministic and non-deterministic optimization and knows how to use them in solving optimization problems in engineering field. Student knows how to formulate optimization problems and how to select a proper optimization method. | — | — | C-1 | T-A-3, T-A-5, T-A-6, T-A-2, T-A-1, T-A-4 | M-2 | S-1 |
Zamierzone efekty kształcenia - inne kompetencje społeczne i personalne
| Zamierzone efekty kształcenia | Odniesienie do efektów kształcenia dla kierunku studiów | Odniesienie do efektów zdefiniowanych dla obszaru kształcenia | Cel przedmiotu | Treści programowe | Metody nauczania | Sposób oceny |
|---|---|---|---|---|---|---|
| WM-WTiICh_2-_null_K01 Student can solve simple task independently or in a group | — | — | C-1 | T-W-7, T-W-4, T-W-8, T-A-3, T-A-5, T-W-3, T-A-6, T-W-9, T-A-2, T-W-6, T-W-12, T-A-1, T-W-5, T-W-10, T-W-13, T-W-1, T-W-2, T-A-4, T-W-11 | M-1, M-2 | S-2, S-1 |
Kryterium oceny - wiedza
| Efekt kształcenia | Ocena | Kryterium oceny |
|---|---|---|
| WM-WTiICh_2-_null_W01 Student has theoretical knowledge of the theory and methods of optimization which allows the analysis and modeling of data and processes | 2,0 | |
| 3,0 | Student is able to list and explain methods used in optimization techniques and select appropriate methods for calculation problems | |
| 3,5 | ||
| 4,0 | ||
| 4,5 | ||
| 5,0 |
Kryterium oceny - umiejętności
| Efekt kształcenia | Ocena | Kryterium oceny |
|---|---|---|
| WM-WTiICh_2-_null_U01 Student knows chosen methods and software tools for deterministic and non-deterministic optimization and knows how to use them in solving optimization problems in engineering field. Student knows how to formulate optimization problems and how to select a proper optimization method. | 2,0 | |
| 3,0 | Student is able to list and explain methods used in optimization techniques and select appropriate methods for calculation problems | |
| 3,5 | ||
| 4,0 | ||
| 4,5 | ||
| 5,0 |
Kryterium oceny - inne kompetencje społeczne i personalne
| Efekt kształcenia | Ocena | Kryterium oceny |
|---|---|---|
| WM-WTiICh_2-_null_K01 Student can solve simple task independently or in a group | 2,0 | |
| 3,0 | Student is able to list and explain methods used in optimization techniques and select appropriate methods for calculation problems | |
| 3,5 | ||
| 4,0 | ||
| 4,5 | ||
| 5,0 |
Literatura podstawowa
- Belegundu A. and T. Chandrupatla, Optimization Concepts and Applications in Engineering, Prentice Hall, 1999
- Gen, M. and R. Cheng, Genetic Algorithms and Engineering Optimization, Wiley, 2000
- Edgar, T.F., Himmelblau, D.M., L.S. Lasdon, Optimization of Chemical Processes, McGraw Hill, 2011
Literatura dodatkowa
- Fletcher R., Practical Methods of Optimization, John Wiley, 1980
- Luenberger, David G., Ye, Yinyu, Linear and Nonlinear Programming, Springer, 2008