Code: 132MMO Modern Methods of Optimization
Lecturer: doc. Ing. Matìj Lep¹ Ph.D. Weekly load: 1P+1C Completion: A
Department: 11132 Credits: 2 Semester: W
Description:
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.
Contents:
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
Seminar contents:
Example of portfolio management
Mathematical Programming
Traveling Salesman Problem and Simulated Annealing
Genetic Algorithms
Genetic Programming
Recommended literature:
!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.
Keywords:
mathematical programming, gradient based methods, direct search methods, evolutionary algorithms, genetic algorithms, design of experiments, meta-models, genetic programming

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