Navigation

13M071OOA - Basic optimization algorithms in engineering

Course specification
Course title Basic optimization algorithms in engineering
Acronym 13M071OOA
Study programme Electrical Engineering and Computing
Module Microwave Engineering
Type of study master academic studies
Lecturer (for classes)
Lecturer/Associate (for practice)
Lecturer/Associate (for OTC)
    ESPB 6.0 Status elective
    Condition None.
    The goal Detailed explanation of basic optimization algorithms commonly used in engineering practice.
    The outcome Training for practical applications of optimization algorithms in engineering problems and scientific research.
    Contents
    Contents of lectures Review of basic terms and the outline of the theory of solving nonlinear systems of equations as a basis for application of optimization algorithms in engineering. Classifications of optimization algorithms. Random search, systematic (grid) search, gradient method, Nelder-Mead simplex, genetic algorithm, simulated annealing, particle swarm optimization. Pareto front and its estimation by using optimization algorithms.
    Contents of exercises Individual projects.
    Literature
    1. Z. Michalewicz, D.B. Fogel, How to Solve It: Modern Heuristics, Springer; 2nd edition, 2004.
    2. D.E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley Professional, 1989.
    Number of hours per week during the semester/trimester/year
    Lectures Exercises OTC Study and Research Other classes
    3 1
    Methods of teaching Lectures, tests, homeworks and individual projects.
    Knowledge score (maximum points 100)
    Pre obligations Points Final exam Points
    Activites during lectures 70 Test paper 30
    Practical lessons Oral examination
    Projects
    Colloquia
    Seminars