ESF:MPM_OMVE Optimization Methods - Course Information
MPM_OMVE Optimization Methods
Faculty of Economics and AdministrationAutumn 2017
- Extent and Intensity
- 2/2/0. 8 credit(s). Type of Completion: zk (examination).
- Teacher(s)
- Ing. Mgr. Markéta Matulová, Ph.D. (lecturer)
Ing. Mgr. Markéta Matulová, Ph.D. (seminar tutor)
Mgr. Eva Mrázková (seminar tutor) - Guaranteed by
- Ing. Mgr. Markéta Matulová, Ph.D.
Department of Applied Mathematics and Computer Science – Faculty of Economics and Administration
Contact Person: Lenka Hráčková
Supplier department: Department of Applied Mathematics and Computer Science – Faculty of Economics and Administration - Timetable
- Wed 12:50–14:30 P104
- Timetable of Seminar Groups:
- Prerequisites
- ! BPM_OMVE Optimization Methods
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 36 student(s).
Current registration and enrolment status: enrolled: 0/36, only registered: 0/36, only registered with preference (fields directly associated with the programme): 0/36 - fields of study / plans the course is directly associated with
- Business Management (programme ESF, M-EKM)
- Business Management (programme ESF, N-EKM)
- Business Informatics (programme ESF, N-SI)
- Course objectives
- The course aims to deepen the knowledge of mathematical tools needed to solve the economic problems and to familiarize students with common types of optimization problems and show some basic methods for their solution (especially the simplex method for linear optimization).
- 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
- solving practical problems using software ( MS Excel, optionally Maple, Matlab and its Optimization toolbox). - Syllabus
- Linear programming
- Integer and goal programming
- Applications: distribution problem, matching problem, etc.
- Optimization in graphs
- Multicriteria decision analysis
- Data envelopment analysis
- Essentials of nonlinear programming
- Literature
- required literature
- JABLONSKÝ, Josef. Operační výzkum : kvantitativní modely pro ekonomické rozhodování. 3. vyd. Praha: Professional Publishing, 2007, 323 s. ISBN 9788086946443. info
- DLOUHÝ, Martin. Modely hodnocení efektivnosti produkčních jednotek. Edited by Josef Jablonský. 1. vyd. Praha: Professional Publishing, 2004, 183 s. ISBN 8086419495. info
- recommended literature
- PLEVNÝ, Miroslav and Miroslav ŽIŽKA. Modelování a optimalizace v manažerském rozhodování. Vyd. 2. Plzeň: Západočeská univerzita, 2010, 296 s. ISBN 9788070439333. info
- GROS, Ivan and Jakub DYNTAR. Matematické modely pro manažerské rozhodování. 2. upravené a rozšířené. Praha: Vysoká škola chemicko-technologická v Praze, 2015, 303 stran. ISBN 9788070809105. info
- Teaching methods
- Theoretical training includes lectures, practical exercises 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. 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
- Czech
- Further Comments
- Study Materials
The course is taught annually.
- Enrolment Statistics (Autumn 2017, recent)
- Permalink: https://is.muni.cz/course/econ/autumn2017/MPM_OMVE