MATH285 Optimization
Credits (ECTS):10
Course responsible:Ole Løseth Elvetun, Bjørn Fredrik Nielsen
Campus / Online:Taught campus Ås
Teaching language:Engelsk
Course frequency:Annually
Nominal workload:125 hours of theory (Lectures and self-study). 125 hours for discussion, exercies and exam preparation
Teaching and exam period:This course starts in the spring parallel. This course has teaching/evaluation in spring parallel.
About this course
The course gives an introduction to the field of optimization, where we will cover four main topics:
- Basic concepts
- Convexity
- Lines and hyperplanes
- Taylor’s theorem
- Unconstrained optimization
- Optimality conditions
- Search methods (Gradient methods and Newton’s method)
- Linear programming
- Standard form
- Inequalities and slack variables
- Simplex method
- Duality
- Non-linear constrained optimization
- Optimality conditions
- Convex optimization
- Solution algorithms
Learning outcome
The students are to learn the basic theory of optimization. More specifically, they are expected to:
- Explain basic concepts and results from the theory
- Solve simple problems analytically
- Recognize different types of optimization problems
- Be able to implement a set of known algorithms in order to solve optimization problems numerically
- The teaching will be given as lectures and exercises with an assistant teacher present.
- The students can either contact the teacher in his/her office, by telephone or by e-mail
- MATH111, MATH112, MATH113, MATH280 and INF100/INF120.
- None.
- Final written examination, 3.5 hours. A -E / failed
Written exam Grading: Letter grades Permitted aids: A1 No calculator, no other aids - The external and internal examiner jointly prepare the exam questions and the correction manual. The external examiner reviews the internal examiner's examination results by correcting a random sample of candidate's exams as a calibration according to the Department's guidelines for examination markings.
- Lectures: 4 hours per week. Exercises: 2 hours per week.
- Special requirements in Science