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13S074IOA - Optimization algorithms in engineering

Course specification
Course title Optimization algorithms in engineering
Acronym 13S074IOA
Study programme Software Engineering
Module
Type of study bachelor academic studies
Lecturer (for classes)
Lecturer/Associate (for practice)
Lecturer/Associate (for OTC)
ESPB 6.0 Status elective
Condition None.
The goal Introduction to widely used classes of optimization algorithms commonly used in engineering and IT applications.
The outcome Students will be able to apply outlined optimization algorithms for solving practical problems.
Contents
Contents of lectures Terminology. Formal definition of an optimization problem. Classification of optimization problems. Random search, systematic search, traditional methods, simplex algorithm, genetic algorithm, simulated annealing, particle swarm optimization and differential evolution. Multicriteria optimization. Pareto front and its estimation using optimization algorithms. Examples of practical applications.
Contents of exercises Computer oriented work and individual projects.
Literature
  1. Z. Michalewicz, D.B. Fogel, How to Solve It: Modern Heuristics, Springer; 2nd edition, 2004. (Original title)
  2. Xin-She Yang, Engineering Optimization: An Introduction with Metaheuristic Applications, Wiley, 2010. (Original title)
  3. D.E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley Professional, 1989. (Original title)
Number of hours per week during the semester/trimester/year
Lectures Exercises OTC Study and Research Other classes
2 2 1
Methods of teaching Lectures, tests, homeworks and individual projects.
Knowledge score (maximum points 100)
Pre obligations Points Final exam Points
Activites during lectures Test paper 30
Practical lessons 30 Oral examination
Projects
Colloquia 40
Seminars