SF1811 Optimization 6.0 credits
Optimeringslära
Educational level
First cycleAcademic level (A-D)
CSubject area
Mathematics
Techonology
Grade scale
A, B, C, D, E, FX, F
Course offerings
Spring 13 for programme students
Periods
Spring 13 P3 (6.0 credits)
Application code
60845Start date
2013 week: 2End date
2013 week: 11Language of instruction
EnglishCampus
KTH CampusNumber of lectures
28 (preliminary)Number of exercises
16 (preliminary)Tutoring time
DaytimeForm of study
NormalNumber of places
No limitationSchedule
Schedule (new window)Course responsible
Per Enqvist <penqvist@kth.se>
Target group
CTFYS, CINEK, CELTE
Part of programme
Autumn 13 for programme students
Periods
Autumn 13 P2 (6.0 credits)
Application code
50577Start date
2013 week: 45End date
2014 week: 3Language of instruction
EnglishCampus
KTH CampusNumber of lectures
28 (preliminary)Number of exercises
16 (preliminary)Tutoring time
DaytimeForm of study
NormalNumber of places
No limitationSchedule
Schedule (new window)Course responsible
Krister Svanberg <krille@kth.se>
Target group
Bachelor students with interest in applied mathematics,
Master students in Applied and Computational Mathematics,
Master students in Aerospace Engineering,
Master students in Systems, Control and Robotics.
Part of programme
Learning outcomes
The overall purpose of the course is that the student should get well acquainted with basic concepts, theory, models and solution methods for optimization. Further, the student should get basic skills in modelling and computer based solving of various applied optimization problems.
Course main content
Examples of applications and modelling training. Basic concepts and theory for optimization, in particular theory for convex problems.
Some linear algebra in R^n, in particular bases for the four fundamental subspaces corresponding to a given matrix, and LDLT-factorization of a symmetric definite matrix.
Linear optimization, including duality theory.
Optimization of flows in networks.
Quadratic optimization with linear constraints.
Linear least squares problems, in particular minimum norm solutions.
Unconstrained nonlinear optimization, in particular nonlinear least squares problems.
Optimality conditions for constrained nonlinear optimization, in particular for convex problems.
Lagrangian relaxation.
Eligibility
SF1604 Linear algebra,
SF1602 + SF1603 Calculus.
Literature
Linear and Nonlinear Programming by Nash and Sofer, McGraw-Hill, and some lecture notes.
Examination
- TEN1 - Examination, 6.0 credits, grade scale: A, B, C, D, E, FX, F
Requirements for final grade
A written examination (TEN1; 6 university credits).
Offered by
SCI/Mathematics
Examiner
Per Enqvist <penqvist@kth.se>
Supplementary information
SF1811 is today identical to SF1841, with common lectures and examination.
Add-on studies
SF2812, SF2822.
Version
Course plan valid from:
Autumn 08.
Examination information valid from:
Autumn 07.
