Course detail
Quantitative methods
FP-BQMEAcad. year: 2022/2023
The course Quantitative Methods acquaints students with selected quantitative methods that are used as a support for decision-making.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Department
Offered to foreign students
Learning outcomes of the course unit
Prerequisites
Co-requisites
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
1. Successful completion of the semester project within the specified deadline.
2. Successful completion of credit test.
A maximum of 100 points may be obtained with a maximum of 50 points for credit test, 25 points for the semester project and 25 points for an eventual correction test. A minimum of 50 points need to be achieved for the credit.
Examination Requirements:
1. Successful completion of the exam test.
The exam is carried out in writing. For its successful completion it is necessary to reach min. 50% out of a possible score of the exam.
Overall evaluation of the course is based on the results obtained by exam with possible reference to the results obtained during the semester.
Course curriculum
2. Mathematical modeling (model, model classification, survey models, mathematical programming model).
3. Linear Programming (formulation technique of linear programming, types of linear programming problems, the general model of linear programming).
4. Formulation of a mathematical model of linear programming (job production planning, transportation problem, assigning the problem).
5. Formulation of a mathematical model of linear programming (mixing problem, nutritional problems, the task of cutting materials, scheduling commercials, portfolio optimization).
6. Solving linear programming problems (graphical, algebraic, using MS Excel).
7. Methods of network analysis (introduction to the topic of project management, the construction of a network graph).
8. Time analysis of AOA deterministic network graphs.
9.Time analysis of AOA stochastic network graphs.
10. Time analysis AON network graphs. The construction of the project schedule.
11. Source project analysis. Dependence times and project costs.
12. Time analysis generalized network graph.
13. Software support of project management.
Work placements
Aims
Specification of controlled education, way of implementation and compensation for absences
Recommended optional programme components
Prerequisites and corequisites
Basic literature
RAIS, K, DOSTÁL, P. Operational Research. CERM. Brno: CERM Akademické nakladatelství, 2008. 84 p. ISBN: 978-80-214-3437-0 (EN)
Recommended reading
MATEO, J.R.S.C. Management Science, Operations Research and Project Management: Modelling, Evaluation, Scheduling, Monitoring. Farnham: Taylor & Francis Group, 2015, 227 p. ISBN 9781472426437. (EN)
YADAV, S.R., MALIK, A.K. Operations Research. New Delhi, India: Oxford University Press, 2014. 691 p. ISBN 978-0-19-809618-4. (EN)
Classification of course in study plans
Type of course unit
Lecture
Teacher / Lecturer
Syllabus
2. Formulation of a mathematical model of linear programming.
3. Formulation of a mathematical model of linear programming.
4. Solving linear programming problems.
5. Introduction to project management.
6. Time analysis of deterministic network graphs.
7. Time analysis of stochastic network graphs.
8. Construction of project schedule.
9. Resource analysis of the project.
10. Time analysis of AON (Activity-On-Node) network graphs.
11. Time analysis of generalized network graph.
12. Theory of decision making.
13. System science.
Exercise
Teacher / Lecturer
Syllabus
2. Formulation of a mathematical model of linear programming.
3. Graphical solving of linear programming problems.
4. Time analysis of deterministic network graph.
5. Time analysis of stochastic network graph.
6. Check test.
7. Correction test.