FSI-0OMAcad. year: 2020/2021
The course presents fundamental mathematical models and methods for solving of optimization engineering problems. It is based on the author's experience with similar courses at the EU and US universities (Computer-Aided Optimization). It is suitable for students interested in the solution of such problems coming from various specializations and years of study. Examples of typical problems involve cases studied and solved within the framework of BUT and FME projects. Particular instances are solved by using a suitable software (MS Excel, Matlab, GAMS aj.). Modelling rules are systematicaly applied: problem formulation and analysis, model building and classification, the use of theory, transforamtions and algorithms, solution analysis and interpretation. The examples of linear, network, nonlinear, integer, dynamic and uncertain models are introduced.
Learning outcomes of the course unit
Although the course is designed for mathematical engineers, it is useful also for engineering students dealing with optimization problems.
Basic concepts of calculus, linear algebra, and programming.
Recommended optional programme components
Recommended or required reading
GAMS User's Guide, GAMS Corp. 2017 (EN)
GAMS Solver's Guide GAMS Corp., 2017 (EN)
Williams, H.P. Model Building in Mathematical Programming, 4th edition. J.Wiley and Sons, 2012. (EN)
Planned learning activities and teaching methods
The course is taught through exercises which are focused on practical topics presented in lectures.
Assesment methods and criteria linked to learning outcomes
The student is asked to participate on the solution of proposed problems.
Language of instruction
The course objective is to emphasize optimization modelling and solution methods related knowledge. Computer-aided optimization is focused.
Specification of controlled education, way of implementation and compensation for absences
The active participation at seminars is assumed.
Type of course unit
26 hours, compulsory
Teacher / Lecturer
Basic models (applied in logistics)
Linear models (production related applications)
Special (network flow and integer) models (transportation problems)
Nonlinear models (aplikace norem)
General models (parametric, multicriteria, nondeterministic,
Course participance is obligatory.