Modern Methods of Optimization
Code  Completion  Credits  Range  Language 

132MMO  Z  2  1P+1C 
 Lecturer:
 Matěj Lepš (guarantor)
 Tutor:
 Matěj Lepš (guarantor)
 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
Multimodal optimization, comparison of optimization algorithms
Multiobjective optimization, constrained optimization
Metamodeling
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 9781461469407.
!A. E. Eiben, J. E. Smith. Introduction to Evolutionary Computing. Springer, 2003, ISBN 9783662050941.
!J. Dréo, A. Pétrowski, P. Siarry, E. Taillard, A. Chatterjee. Metaheuristics for Hard Optimization: Methods and Case Studies. Springer, 2005, ISBN 9783540309666.
!Weise, Thomas, et al. „Why is optimization difficult?“ NatureInspired Algorithms for Optimisation. Springer Berlin Heidelberg, 150, 2009, ISBN 9783642002670.
 Note:
 Timetable 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 Thu Fri  Timetable for summer semester 2019/2020:
 Timetable is not available yet
 The course is a part of the following study plans:

 Building Structures (compulsory elective course)
 Civil Engineering, branch Building Structures (compulsory elective course)
 Civil Engineering, branch Building Structures (compulsory elective course)
 Building Structures (compulsory elective course)
 Building Structures (compulsory elective course)
 Civil Engineering, branch Building Structures (compulsory elective course)
 Civil Engineering, branch Building Structures (compulsory elective course)