SubjectsSubjects(version: 855)
Course, academic year 2019/2020
  
Engineering Optimalization - P445007
Title: Inženýrská Optimalizace
Guaranteed by: Department of Computing and Control Engineering (445)
Actual: from 2019
Semester: both
Points: 0
E-Credits: 0
Examination process:
Hours per week, examination: 3/0 other [hours/week]
Capacity: winter:unlimited / unknown (unknown)
summer:unknown / unknown (unknown)
Min. number of students: unlimited
Language: Czech
Teaching methods: full-time
Level:  
For type: doctoral
Note: course is intended for doctoral students only
can be fulfilled in the future
you can enroll for the course in winter and in summer semester
Guarantor: Kukal Jaromír doc. Ing. Ph.D.
Interchangeability : D445005
Is interchangeable with: AP445007
Annotation -
Last update: Mareš Jan doc. Ing. Ph.D. (07.06.2018)
The course deals with modern methods and tool of optimization. The aim of the course is to use selected lgorthms for solving real problems from technological praxis. For the exam it is necessary to propose a draft of publication form the field of disertation thesis.
Aim of the course -
Last update: Mareš Jan doc. Ing. Ph.D. (07.06.2018)

Students will be able to:

  • use selected methods of optimosation to solve a real problém form technological praxis,
  • use selected methods of artificial intelligence to solve problems of global optimisation,
Literature -
Last update: Kukal Jaromír doc. Ing. Ph.D. (04.09.2018)

R: Himmelblau, D. M.: Applied Nonlinear Programming. McGraw-Hill, New York 1972. ISBN 0-07-028921-2.

A: Venkataraman P.: Applied Optimization with MATLAB Programming. Wiley, New York. 2002. ISBN 0-471-34958-5.

A: Lange, K.: Optimization (2nd edition), Springer, New York 2013. ISBN 978-1-4614-5837-1.

Learning resources -
Last update: Mareš Jan doc. Ing. Ph.D. (07.06.2018)

www.honeywellprocess.com/

www.mathworks.com/

Teaching methods -
Last update: Mareš Jan doc. Ing. Ph.D. (07.06.2018)

lectures, project and solving of case stidies

Syllabus -
Last update: Mareš Jan doc. Ing. Ph.D. (07.06.2018)

1. Optimisation process, aims. Theoretical introduction

2. Local optimisation, analytical and nunerical tools overview.

3. Linear, quadratic and nonlinear programming.

4. Discrete and global optimisation. Genetic and evolution algorithms.

5. Using Optimization Toolbox and Global Optimization Toolbox.

Entry requirements -
Last update: Mareš Jan doc. Ing. Ph.D. (07.06.2018)

none

Registration requirements -
Last update: Mareš Jan doc. Ing. Ph.D. (07.06.2018)

none

Course completion requirements -
Last update: Mareš Jan doc. Ing. Ph.D. (07.06.2018)

3 individual projects: 0 - 25 bodů

Oral exam: 0-75 bodů

100-90 A, 89-80 B, 79-70 C, 69-60 D, 59-50 E, méně než 50 F.

Coursework assessment
Form Significance
Defense of an individual project 30
Oral examination 70

 
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