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CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2019/2020

Modern Methods of Optimization

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Code Completion Credits Range Language
132YMMO Z 2 1P+1C Czech
Lecturer:
Jan Zeman, Adéla Hlobilová, Matěj Lepš
Tutor:
Jan Zeman, Adéla Hlobilová, Matěj Lepš
Supervisor:
Department of Mechanics
Synopsis:

The course is aimed at an overview of numerical optimization methods applicable not only in the Civil Engineering area. The emphasis is put more on the introduction of driving principles, however, practical applications in MATLAB environment are also conducted during exercises.

Requirements:

no prerequisities

Syllabus of lectures:

Introduction to Global optimization

Mathematical Programming I

Mathematical Programming II

Mathematical Programming III

Direct Search methods, Simulated Annealing, Threshold Acceptance

Genetic Algorithms

Evolution Strategies, Differential Evolution, PSO and ACO

Parallel Evolutionary Algorithms and No free lunch theorem

Multi-modal optimization, comparison of optimization algorithms

Multi-objective optimization, constrained optimization

Meta-modeling

Genetic Programming

Examples of engineering applications

Syllabus of tutorials:

Example of portfolio management

Mathematical Programming

Traveling Salesman Problem and Simulated Annealing

Genetic Algorithms

Genetic Programming

Study Objective:

The goal of the course is to obtain an understanding of basic principles and terminology of mathematical optimization as well as approaches to global stochastic methods. The theoretical exposition will be complemented with practical solution of selected optimization problems using publicly available toolboxes in MATLAB environment.

Study materials:

!Search Methodologies: Introductory Tutorials in Optimization and Decision Support Techniques, E. K. Burke, G. Kendall (Editors), Springer, 2014, ISBN 978-1-4614-6940-7.

!A. E. Eiben, J. E. Smith. Introduction to Evolutionary Computing. Springer, 2003, ISBN 978-3-662-05094-1.

!J. Dréo, A. Pétrowski, P. Siarry, E. Taillard, A. Chatterjee. Metaheuristics for Hard Optimization: Methods and Case Studies. Springer, 2005, ISBN 978-3-540-30966-6.

!Weise, Thomas, et al. „Why is optimization difficult?“ Nature-Inspired Algorithms for Optimisation. Springer Berlin Heidelberg, 1-50, 2009, ISBN 978-3-642-00267-0.

Note:
Further information:
http://mech.fsv.cvut.cz/~leps/teaching/mmo/index.html
Time-table for winter semester 2019/2020:
06:00–08:0008:00–10:0010:00–12:0012:00–14:0014:00–16:0016:00–18:0018:00–20:0020:00–22:0022:00–24:00
Mon
Tue
Fri
roomTH:B-373

18:00–18:50
(lecture parallel1)
Thákurova 7 (FSv-budova A)
B373
roomTH:B-373

19:00–19:50
(lecture parallel1
parallel nr.101)

Thákurova 7 (FSv-budova A)
B373
Thu
Fri
Time-table for summer semester 2019/2020:
Time-table is not available yet
The course is a part of the following study plans:
Data valid to 2020-04-06
For updated information see http://bilakniha.cvut.cz/en/predmet24872005.html