Course detail
Quantitative methods
FP-KVMAcad. year: 2012/2013
The Quantitative Methods course will instruct students on the decision-making theory, modelling, methods of operation research and its applications. The main part of the course focuses on formulating mathematical models of typical linear programming problems and on applying network analysis methods to project management.
Language of instruction
Czech
Number of ECTS credits
4
Mode of study
Not applicable.
Guarantor
Department
Learning outcomes of the course unit
After completing the course, the students will be capable of solving optimization problems and decision-making problems in various application areas.
Prerequisites
Basics of mathematics particularly linear algebra.
Co-requisites
Not applicable.
Planned learning activities and teaching methods
Teaching methods depend on the type of course unit as specified in the article 7 of BUT Rules for Studies and Examinations.
Assesment methods and criteria linked to learning outcomes
The following conditions have to be met by a student to be given the credit:
1. A successful semestral project has to be submitted by a deadline and presented.
2. Active participation in seminars and partial projects submitted for approval on three dates.
A maximum of 100 points may be obtained with a maximum of 60 points for check tests written during seminars, 15 points for the semestral project and 25 points for a credit test. A minimum of 50 points need to be achieved for the credit.
Requirements of the test: Theoretical knowledge from lectures and its practical applications. The exam consists of a theoretical part and a practical one including problem solving.
1. A successful semestral project has to be submitted by a deadline and presented.
2. Active participation in seminars and partial projects submitted for approval on three dates.
A maximum of 100 points may be obtained with a maximum of 60 points for check tests written during seminars, 15 points for the semestral project and 25 points for a credit test. A minimum of 50 points need to be achieved for the credit.
Requirements of the test: Theoretical knowledge from lectures and its practical applications. The exam consists of a theoretical part and a practical one including problem solving.
Course curriculum
1. Managerial decision-making
2. Systems science
3. Modelling
4. Linear programming
5. Network analysis
2. Systems science
3. Modelling
4. Linear programming
5. Network analysis
Work placements
Not applicable.
Aims
The course aims to acquaint the students with methods of operations research and their applications. Emphasis is placed on formulating the mathematical models of typical linear programming problems and problems of network analysis.
Specification of controlled education, way of implementation and compensation for absences
A student’s own work on the tasks assigned is checked. In the event of an excused absence from a seminar, a student may be given a substitute condition, which mostly consists of a substitute project assigned.
Recommended optional programme components
Not applicable.
Prerequisites and corequisites
Not applicable.
Basic literature
DOSKOČIL, R. Kvantitativní metody. 2.vyd. Brno: Akademické nakladatelství CERM, 2019, 260 s. ISBN 978-80-214-5716-4. (CS)
Recommended reading
ANDERSON, D.R. et al. Quantitative Methods for Business. 13th ed. Boston: Cengage Learning, 2016, 914 p. ISBN-13: 978-1-285-86631-4. (EN)
GROS, I. Kvantitativní metody v manažerském rozhodování. 1. vyd. Praha: Grada Publishing a.s., 2003, 432 s. ISBN 80-247-0421-8. (CS)
JABLONSKÝ, J. Operační výzkum: kvantitativní modely pro ekonomické rozhodování. 3. vyd. Praha: Professional Publishing, 2007, 323 s. ISBN 978-80-86946-44-3. (CS)
MATEO, J.R.S.C. Management Science, Operations Research and Project Management: Modelling, Evaluation, Scheduling, Monitoring. Farnham: Taylor & Francis Group, 2015, 227 (EN)
PLEVNÝ, M.; ŽIŽKA, M. Modelování a optimalizace v manažerském rozhodování. 2.vyd. Plzeň: Západočeská univerzita v Plzni, 2010, 296 s. ISBN 978-80-7043-933-3. (CS)
GROS, I. Kvantitativní metody v manažerském rozhodování. 1. vyd. Praha: Grada Publishing a.s., 2003, 432 s. ISBN 80-247-0421-8. (CS)
JABLONSKÝ, J. Operační výzkum: kvantitativní modely pro ekonomické rozhodování. 3. vyd. Praha: Professional Publishing, 2007, 323 s. ISBN 978-80-86946-44-3. (CS)
MATEO, J.R.S.C. Management Science, Operations Research and Project Management: Modelling, Evaluation, Scheduling, Monitoring. Farnham: Taylor & Francis Group, 2015, 227 (EN)
PLEVNÝ, M.; ŽIŽKA, M. Modelování a optimalizace v manažerském rozhodování. 2.vyd. Plzeň: Západočeská univerzita v Plzni, 2010, 296 s. ISBN 978-80-7043-933-3. (CS)
Classification of course in study plans
Type of course unit
Lecture
26 hod., optionally
Teacher / Lecturer
Syllabus
1. Introduction to linear programming, linear programming problem formulation workflow.
Formulating a mathematical model of the production programme linear programming problem.
2. Formulating a mathematical model of the distribution problem in linear programming.
3. Formulating a mathematical model of the cutting stock linear programming problem
– other types.
4. Linear programming problem solution – graphical, algebraic methods, software-based
solutions.
5. Project management – introduction, constructing a network graph.
6. Time analysis of edge-weighted deterministic network graphs (CPM).
7. Time analysis of stochastic network graphs (PERT).
8. Producing a timetable from a network graph, analyzing project resources.
9. Time analysis of node-weighted deterministic network graphs (MPM).
10.Time analysis of a generalized graph (GERT).
11.Theory of decision making.
12.System science, mathematical modelling.
13.Practical examples of using methods of operations research.
Formulating a mathematical model of the production programme linear programming problem.
2. Formulating a mathematical model of the distribution problem in linear programming.
3. Formulating a mathematical model of the cutting stock linear programming problem
– other types.
4. Linear programming problem solution – graphical, algebraic methods, software-based
solutions.
5. Project management – introduction, constructing a network graph.
6. Time analysis of edge-weighted deterministic network graphs (CPM).
7. Time analysis of stochastic network graphs (PERT).
8. Producing a timetable from a network graph, analyzing project resources.
9. Time analysis of node-weighted deterministic network graphs (MPM).
10.Time analysis of a generalized graph (GERT).
11.Theory of decision making.
12.System science, mathematical modelling.
13.Practical examples of using methods of operations research.
Exercise
26 hod., compulsory
Teacher / Lecturer
Syllabus
1. Introductory information, credit requirements, outlining the contents of the seminar.
2. Formulating a mathematical model of the production programme linear programming problem.
3. Formulating a mathematical model of the distribution problem in linear programming.
4. Formulating a mathematical model of the cutting stock linear programming problem.
5. Formulating a mathematical model of linear programming problems – other types.
Graphical solving of linear programming problems.
6. Check test I.
7. Project management – introduction, setting up a network graph.
8. Time analysis of edge-weighted deterministic network graphs (CPM).
9. Time analysis of stochastic network graphs (PERT).
10.Producing a timetable from a network graph, analyzing project resources.
11.Check test II.
12.Check – PROJECT presentation.
13.Summarizing results, granting credits, substitute credit tests – Check test III.
2. Formulating a mathematical model of the production programme linear programming problem.
3. Formulating a mathematical model of the distribution problem in linear programming.
4. Formulating a mathematical model of the cutting stock linear programming problem.
5. Formulating a mathematical model of linear programming problems – other types.
Graphical solving of linear programming problems.
6. Check test I.
7. Project management – introduction, setting up a network graph.
8. Time analysis of edge-weighted deterministic network graphs (CPM).
9. Time analysis of stochastic network graphs (PERT).
10.Producing a timetable from a network graph, analyzing project resources.
11.Check test II.
12.Check – PROJECT presentation.
13.Summarizing results, granting credits, substitute credit tests – Check test III.