ZUT - Krajowe Ramy Kwalifikacji / Rok 2018/2019 / Administracja Centralna Uczelni / Wymiana międzynarodowa (S2) / Sylabus przedmiotu

Administracja Centralna Uczelni - Wymiana międzynarodowa (S2)

Kierunek studiów	Wymiana międzynarodowa
Forma studiów	studia stacjonarne	Poziom	drugiego stopnia
Tytuł zawodowy absolwenta
Obszary studiów	—
Profil
Moduł	—
Przedmiot	Practical Methods of Optimization
Specjalność	przedmiot wspólny
Jednostka prowadząca	Katedra Konstrukcji, Mechaniki i Technologii Okrętów
Nauczyciel odpowiedzialny	Zbigniew Sekulski <Zbigniew.Sekulski@zut.edu.pl>
Inni nauczyciele
ECTS (planowane)	6,0	ECTS (formy)	6,0
Forma zaliczenia	zaliczenie	Język	angielski
Blok obieralny	—	Grupa obieralna	—

Forma dydaktyczna	KOD	Semestr	Godziny	ECTS	Waga	Zaliczenie
ćwiczenia audytoryjne	A	1	30	3,5	0,60	zaliczenie
wykłady	W	1	30	2,5	0,40	zaliczenie

KOD	Wymaganie wstępne
W-1	Linear algebra, differential calculations.

KOD	Cel modułu/przedmiotu
C-1	To learn basic concepts of continuous optimization.

KOD	Treść programowa	Godziny
ćwiczenia audytoryjne
T-A-1	Solwing some practical examples of unconstrained and constrained optimisation problems.	30
		30
wykłady
T-W-1	Introduction: what is optimization problem?	2
T-W-2	Definition of mathematical formulation of continuous optimization (necessary and sufficient conditions of local optimality, concept of matrix positive definition, convex and concave functions).	2
T-W-3	General formulation of optimization problem.	2
T-W-4	Review and discussion of optimization problems.	2
T-W-5	General formulation of optimization algorithm.	2
T-W-6	Review and discussion of classical optimization algorithms.	2
T-W-7	Detailed formulation of selected representative optimization algorithms classified by the extent of information they require (nonderivative methods, gradient methods, Newton-Raphson methods).	8
T-W-8	Constraints in optimization problems.	2
T-W-9	Optimization methods of constrained problems (Kuhn-Tucker conditions, Lagrange multipliers method, penalty function methods).	6
T-W-10	Evaluation of knowledge.	2
		30

KOD	Forma aktywności	Godziny
ćwiczenia audytoryjne
A-A-1	Participation in classes.	30
A-A-2	Preparation of homeworks.	65
A-A-3	Preparation to skills evaluation.	10
		105
wykłady
A-W-1	Participation in classes.	30
A-W-2	Self study.	34
A-W-3	Preparation to knowledge evaluation.	10
		74

dla tego przedmiotu nie są określone metody nauczania ani narzędzia dydaktyczne

dla tego przedmiotu nie są określone sposoby oceny

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-WTMiT_2-_??_W01 After this course, the student will be able to: (1) estimate the actual complexity of nonlinear optimization problems; (2) apply lower complexity bounds, which establish the limits of performance of optimization method; (3) explain the main principles for constructing the optimal methods for solving different types of optimization problems, (4) use the main problem classes (general nonlinear problems, smooth convex problems, nonsmooth convex problems, structural optimization); (5) understand the rate of convergence of the main optimization methods; (6) two testing computer projects give a possibility to compare the theoretical conclusions and predictions with real performance of minimization / maximization methods.	—	—	—	—	—	—

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-WTMiT_2-_??_U01 The ability to use the acquired knowledge to solve practical problems.	—	—	—	—	—	—

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-WTMiT_2-_??_K01 Improvement of social and personal competencies including self-awareness, self-management, social awareness, relationship skills, responsible decision-making and others. Encouraging dialogue and mutual respect between peoples of different nations, cultures and faiths.	—	—	—	—	—	—

Gill, P.E., Murray, W., Wright, M.H., Practical Optimization, Academic Press, London, 1986
Dennis, J.E., Schnabel, R.B., Numerical Methods for Unconstrained Optimization and Nonlinear Equations, Society for Industrial and Applied Mathematics, Philadelphia, 1996

Nocedal, J., Wright, S.J., Numerical Optimization, Springer, New York, 1999
Osyczka A., Evolutionary Algorithms for Single and Multicriteria Design Optimization, Physica-Verlag, Heidelberg, Germany, 2002

KOD	Treść programowa	Godziny
T-A-1	Solwing some practical examples of unconstrained and constrained optimisation problems.	30
		30

KOD	Treść programowa	Godziny
T-W-1	Introduction: what is optimization problem?	2
T-W-2	Definition of mathematical formulation of continuous optimization (necessary and sufficient conditions of local optimality, concept of matrix positive definition, convex and concave functions).	2
T-W-3	General formulation of optimization problem.	2
T-W-4	Review and discussion of optimization problems.	2
T-W-5	General formulation of optimization algorithm.	2
T-W-6	Review and discussion of classical optimization algorithms.	2
T-W-7	Detailed formulation of selected representative optimization algorithms classified by the extent of information they require (nonderivative methods, gradient methods, Newton-Raphson methods).	8
T-W-8	Constraints in optimization problems.	2
T-W-9	Optimization methods of constrained problems (Kuhn-Tucker conditions, Lagrange multipliers method, penalty function methods).	6
T-W-10	Evaluation of knowledge.	2
		30

KOD	Forma aktywności	Godziny
A-A-1	Participation in classes.	30
A-A-2	Preparation of homeworks.	65
A-A-3	Preparation to skills evaluation.	10
		105

(*) 1 punkt ECTS, odpowiada około 30 godzinom aktywności studenta

KOD	Forma aktywności	Godziny
A-W-1	Participation in classes.	30
A-W-2	Self study.	34
A-W-3	Preparation to knowledge evaluation.	10
		74

(*) 1 punkt ECTS, odpowiada około 30 godzinom aktywności studenta

Pole	KOD	Znaczenie kodu
Zamierzone efekty kształcenia	WM-WTMiT_2-_??_W01	After this course, the student will be able to: (1) estimate the actual complexity of nonlinear optimization problems; (2) apply lower complexity bounds, which establish the limits of performance of optimization method; (3) explain the main principles for constructing the optimal methods for solving different types of optimization problems, (4) use the main problem classes (general nonlinear problems, smooth convex problems, nonsmooth convex problems, structural optimization); (5) understand the rate of convergence of the main optimization methods; (6) two testing computer projects give a possibility to compare the theoretical conclusions and predictions with real performance of minimization / maximization methods.

Pole	KOD	Znaczenie kodu
Zamierzone efekty kształcenia	WM-WTMiT_2-_??_U01	The ability to use the acquired knowledge to solve practical problems.

Pole	KOD	Znaczenie kodu
Zamierzone efekty kształcenia	WM-WTMiT_2-_??_K01	Improvement of social and personal competencies including self-awareness, self-management, social awareness, relationship skills, responsible decision-making and others. Encouraging dialogue and mutual respect between peoples of different nations, cultures and faiths.