Modern Methods of Optimization

Course guarantor:

Matěj Lepš

Lecturer:

Matěj Lepš, Jan Zeman

Tutor:

Matěj Lepš, Jan Zeman

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 2024/2025:

	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
Wed
Thu	roomTH:B-373 08:00–08:50 (lecture parallel1) Thákurova 7 (budova FSv) roomTH:B-373 09:00–09:50 (lecture parallel1 parallel nr.101) Thákurova 7 (budova FSv)
Fri

Time-table for summer semester 2024/2025:

Time-table is not available yet

The course is a part of the following study plans:

• Stavební inženýrství, specializace Pozemní stavby (compulsory elective course)
• Stavební inženýrství, specializace Konstrukce a dopravní stavby (compulsory elective course)
• Stavební Inženýrství - konstrukce a dopravní stavby, specializace Inženýrské konstrukce (compulsory elective course)
• Stavební Inženýrství - konstrukce a dopravní stavby, specializace Dopravní stavby a geotechnika (compulsory elective course)
• Stavební inženýrství - pozemní stavby, specializace Projektování pozemních staveb (compulsory elective course)
• Stavební inženýrství - pozemní stavby, specializace Statika pozemních staveb (compulsory elective course)
• Stavební inženýrství, specializace Pozemní stavby (compulsory elective course)