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CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2023/2024

Local Optimization Methods

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Code Completion Credits Range Language
D01MLO_EN ZK 2P English
Garant předmětu:
Jan Chleboun
Lecturer:
Jan Chleboun
Tutor:
Supervisor:
Department of Mathematics
Synopsis:

The goal is to make students familiar with common methods for the minimization of functions of one or several real variables. Unconstrained as well as constrained minimization are considered. By using software tools (Matlab, SciLab, Octave, Python, etc.), course participants are expected to present a solution to a minimization problem motivated by the subject of their research.

Topics:

Minimization of functions of one real variable.

Unconstrained minimization of functions of several real variables. Conditions for local optimality. Conjugate gradient method, quasi-Newton methods.

Constrained minimization of functions of several real variables. Lagrange multipliers. Conditions for local optimality. Penalty method, active set method, gradient projection method, SQP method (Sequential Quadratic Programming).

Introduction to linear programming, simplex method.

Requirements:
Syllabus of lectures:
Syllabus of tutorials:
Study Objective:
Study materials:
Note:
Time-table for winter semester 2023/2024:
Time-table is not available yet
Time-table for summer semester 2023/2024:
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The course is a part of the following study plans:
Data valid to 2024-07-13
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