P027 Optimization

Faculty of Informatics
Spring 2001
Extent and Intensity
2/1. 3 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium), z (credit).
Teacher(s)
RNDr. Petr Mejzlík, Dr. (lecturer)
Guaranteed by
prof. PhDr. Karel Pala, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: RNDr. Petr Mejzlík, Dr.
Timetable
Mon 14:00–16:50 C525
Prerequisites
M001 Calculus II && M004 Linear Algebra and Geometry II
Prerequisites: mathematical analysis M001 Calculus II and linear algebra M004 Linear Algebra and Geometry II.
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
Syllabus
  • This is a basic course on methods of mathematical optimization and their practical use.
  • Unconstrained optimization: Nelder--Mead method, steepest descent, Newton methods, conjugate gradient, trust region methods. Least squares problem and analysis of experimental data.
  • Linear programming, revised Simplex method, interior point methods. Applications of linear programming. Integer programming, branch and bound method. Dynamic programming.
  • Nonlinear constrained optimization: penalty functions, quadratic programming, sequential quadratic programming method.
  • Global optimization: simulated annealing, genetic algorithms, diffusion equation method.
Language of instruction
Czech
Further Comments
The course is taught annually.
Teacher's information
ftp://ftp.fi.muni.cz:/pub/users/mejzlik/optimalizace/
The course is also listed under the following terms Autumn 1995, Autumn 1996, Spring 1998, Spring 1999, Spring 2000.
  • Enrolment Statistics (recent)
  • Permalink: https://is.muni.cz/course/fi/spring2001/P027