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Course, academic year 2023/2024
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Optimisation I - NEKN012
Title: Optimalizace I
Guaranteed by: Department of Probability and Mathematical Statistics (32-KPMS)
Faculty: Faculty of Mathematics and Physics
Actual: from 2018
Semester: winter
E-Credits: 6
Hours per week, examination: winter s.:4/0, Ex [HT]
Capacity: unlimited
Min. number of students: unlimited
4EU+: no
Virtual mobility / capacity: no
State of the course: cancelled
Language: Czech
Teaching methods: full-time
Teaching methods: full-time
Guarantor: doc. RNDr. Petr Lachout, CSc.
Classification: Mathematics > Optimization
Interchangeability : NMSA403
Is co-requisite for: NEKN026, NEKN003, NEKN035
Is incompatible with: NMAN007, NEKN011
Is pre-requisite for: NEKN005
Is interchangeable with: NMAN007
Annotation -
Last update: G_M (10.10.2001)
Optimization in economy and statistics, introduction to non-linear programming, theory of linear programming with respect to convex analysis and general optimization, overview of available optimization software, matrix games. The contents of the course and seminar is organized so that the lecture could be attended without the seminar.
Aim of the course -
Last update: T_KPMS (22.05.2008)

To give explanation and theoretical background for standard optimization procedures. Students will lern necessary theory and practice their knowladge on numerical examples.

Literature - Czech
Last update: T_KPMS (05.03.2007)

Pracovní text přednášky je k dispozici na WWW-stránce doc. Petra Lachouta.

Ján Plesník, Jitka Dupačová, Milan Vlach.: Lineárne programovanie. Alfa, Bratislava, 1990.

George B. Dantzig, Mukund N. Thapa: Linear programming. 1,2. Springer, New York, 1997.

Dimitri P. Bertsekas: Nonlinear programming. Athena Scientific, Belmont, 1999.

Mokhtar S. Bazaraa, Hanif D. Sherali, C.M. Shetty: Nonlinear programming : theory and algorithms. Wiley, New York, 1993.

Teaching methods -
Last update: G_M (27.05.2008)

Lecture.

Syllabus -
Last update: T_KPMS (25.04.2003)

Optimization in economy and statistics, introduction to non-linear programming, theory of linear programming with respect to convex analysis and general optimization, overview of available optimization software, matrix games.

 
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