BPM_AOME Quantitative Methods for Decision Making

Faculty of Economics and Administration
Spring 2025
Extent and Intensity
2/2/0. 8 credit(s). Type of Completion: zk (examination).
In-person direct teaching
Teacher(s)
Ing. Mgr. Markéta Matulová, Ph.D. (lecturer)
Ing. Mgr. Markéta Matulová, Ph.D. (seminar tutor)
Guaranteed by
Ing. Mgr. Markéta Matulová, Ph.D.
Division of Applied Mathematics and Computer Science – Faculty of Economics and Administration
Contact Person: Mgr. Jana Nesvadbová
Supplier department: Division of Applied Mathematics and Computer Science – Faculty of Economics and Administration
Prerequisites
Basic knowledge of calculus and linear algebra
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 24 student(s).
Current registration and enrolment status: enrolled: 0/24, only registered: 41/24, only registered with preference (fields directly associated with the programme): 37/24
fields of study / plans the course is directly associated with
Course objectives
The course aims to deepen knowledge of mathematical tools needed to solve the economic problems. The main goal is to familiarize students with common types of optimization problems and basic methods for their solution.
Learning outcomes
Student will be able to:
- identify and formulate specific optimization problems that occur in economics, project management, production management, quality management, etc.
- apply the algorithms used to solve these optimization problems
- explain the solution procedure
- solve practical problems using software (MS Excel).
Syllabus
  • Linear programming
  • Simplex method for solving LP
  • Duality and sensitivity analysis
  • Applications: distribution problem
  • Applications: assignment problem, etc.
  • Integer programming
  • Optimization on graphs
  • Project management; methods CPM and PERT
  • Multi-criteria decision analysis
  • Multi-criteria and goal programming
  • Data envelopment analysis I
  • Data envelopment analysis II
Literature
    required literature
  • HILLIER, Frederick S. and Gerald J. LIEBERMAN. Introduction to operations research. 11th ed. New York: McGraw-Hill, 2020. ISBN 1-260-58696-0. info
    recommended literature
  • TAHA, Hamdy A. Operations research : an introduction. 11th ed. Upper Saddle River, N.J.: Prentice Hall, 2022. ISBN 1-259-87299-8. info
  • COOPER, William W., Lawrence M. SEIFORD and Kaoru TONE. Data envelopment analysis : a comprehensive text with models, applications, references and DEA-solver software. Second edition. New York: Springer, 2007, xxxviii, 4. ISBN 9780387452814. info
Teaching methods
Theoretical training: lectures and homework
Instructions: problem solving using computer
Assessment methods
The course is ended by an examination. The prerequisite of successful completion of the course is active participation in seminars. The rating is determined by point gain from the final test and the team project. Any copying, recording or leaking tests, use of unauthorized tools, aids and communication devices, or other disruptions of objectivity of exams (credit tests) will be considered non-compliance with the conditions for course completion as well as a severe violation of the study rules. Consequently, the teacher will finish the exam (credit test) by awarding grade "F" in the Information System, and the Dean will initiate disciplinary proceedings that may result in study termination.
Language of instruction
English
Further Comments
The course is taught annually.
The course is taught: every week.
The course is also listed under the following terms Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024.
  • Enrolment Statistics (recent)
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