MAF01 Numerical optimalisation

Faculty of Science
Spring 2010
Extent and Intensity
2/0/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
doc. RNDr. Ladislav Adamec, CSc. (lecturer)
Guaranteed by
prof. RNDr. Ondřej Došlý, DrSc.
Department of Mathematics and Statistics – Departments – Faculty of Science
Timetable
Tue 16:00–17:50 M4,01024
Prerequisites
Differential calculus in several variables, metric spaces. Basic numerical methods.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The goal of the lecture is to give a description of the most powerfull and state of the art techniques for solving continuous optimization problems.
At the end of this course, students will acquire knowledge of the field of unconstrained numerical optimization in R1 and Rn.
Syllabus
  • 1. Introduction into numerical optimization.
  • 2. Numerical optimization in R1.
  • 3. Unconstrained optimization in Rn.
  • 4. Fundamentals of constrained optimization in Rn.
Literature
  • FLETCHER, R. Practical methods of optimization. 1st ed. Chichester: John Wiley & Sons, 1987, xiv, 436. ISBN 0471915475. info
Teaching methods
Theoretical lectures.
Assessment methods
Oral examination.
Language of instruction
Czech
Further Comments
The course is taught only once.

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