Course detail

Computing Methods in Optimization Problems

FSI-VOU-KAcad. year: 2022/2023

The course introduces to the basic concepts of optimization and the use of appropriate software. Subsequently, optimization problems in engineering are solved. The main content of the course is to recognize and use a suitable model and methods for specific engineering tasks.

Language of instruction

Czech

Number of ECTS credits

Mode of study

Not applicable.

Guarantor

doc. Ing. Jakub Kůdela, Ph.D.

Department

Institute of Automation and Computer Science (ÚAI)

Learning outcomes of the course unit

The student will aquire the ability to recognize a suitable optimization model for a given engineering problem. The student will be able to implement said model in an adequately chosen software and analyze the results.

Prerequisites

Basic of differential and integral calculus, linear algebra, probability and statistics, and programming.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

The explanation of theory, basic principles and illustrative demonstrations on concrete examples will be given in lectures. Exercises will follow the lectures and will be of a computer character.

Assesment methods and criteria linked to learning outcomes

The course will be completed by graded course-unit credit. Students develop a project on a specific topic. Final classification of the course is according to ECTS scale.

Course curriculum

Not applicable.

Work placements

Students will be sent to internships according to contracts and currently offered courses at partner universities.

Aims

The emphasis is on the aquisition of application-oriented of optimization models and methods, and on the use of computers and available software.

Specification of controlled education, way of implementation and compensation for absences

Controlled participation in computer lessons.

Recommended optional programme components

Williams, H.P. Model Building in Mathematical Programming, 4th edition. J.Wiley and Sons, 2012. (EN)
Boyd, S.P. a Vanderberghe, L. Convex Optimization, Cambridge University Press, 2004. (EN)

Prerequisites and corequisites

Not applicable.

Basic literature

Boyd, S.P. a Vandenberghe, L. Convex Optimization, Cambridge University Press, 2004.
Williams, H.P. Model Building in Mathematical Programming, 4th edition. J.Wiley and Sons, 2012.

Recommended reading

Boyd, S.P. a Vandenberghe, L. Convex Optimization, Cambridge University Press, 2004.
Klapka,J. a kol.: Metody operačního výzkumu. FSI, 2001.
Williams, H.P. Model Building in Mathematical Programming, 4th edition. J.Wiley and Sons, 2012.

Elearning

eLearning: currently opened course

Classification of course in study plans

  • Programme B-STR-K Bachelor's

    specialization AIŘ , 3 year of study, winter semester, compulsory

Type of course unit

 

Guided consultation in combined form of studies

22 hod., compulsory

Teacher / Lecturer

doc. Ing. Jakub Kůdela, Ph.D.

Syllabus

1. Introduction to optimization (basic concepts).
2. Software tools for optimization: languages/enviroments: EXCEL, MATLAB, Julia. The use of solvers.
3. - 5. Optimization problems in engineering, types of optimization models (linear, quadratic, convex, etc.)
6. - 7. Integer programming problems – applications in logistics, scheduling, etc.
8. Linearization, modelling with SOS1 and SOS2 variables.
9. Black-box optimization and optimization within a simulation environment.
10. Dynamic optimization models.
11. - 13. Models with uncertain data – stochastic and robust formulations.

Guided consultation

43 hod., optionally

Teacher / Lecturer

doc. Ing. Jakub Kůdela, Ph.D.

Syllabus

The exercise follows the topics discussed in the lecture. The main focus is on software implementation.

Elearning

eLearning: currently opened course