157-9583/01 – Stochastic and fuzzy modelling of decision processes (SMEPe)

Gurantor departmentDepartment of Systems EngineeringCredits10
Subject guarantordoc. Mgr. Ing. František Zapletal, Ph.D.Subject version guarantordoc. Mgr. Ing. František Zapletal, Ph.D.
Study levelpostgraduateRequirementChoice-compulsory type B
YearSemesterwinter + summer
Study languageEnglish
Year of introduction2020/2021Year of cancellation
Intended for the facultiesEKFIntended for study typesDoctoral
Instruction secured by
LoginNameTuitorTeacher giving lectures
ZAP149 doc. Mgr. Ing. František Zapletal, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Examination 28+0
Part-time Examination 28+0

Subject aims expressed by acquired skills and competences

The aim of this subject is to provide methodological basis for decision-making in systems, which are uncertain.

Teaching methods

Individual consultations


Students will be able to choose a suitable approach how to model risk or uncertainty and how to build the corresponding mathematical model. Students will learn especially algorithms of multi-criteria decision making with uncertain or random input data, or with missing data.

Compulsory literature:

CHAVAS, Jean P. Risk Analysis in Theory and Practice, Academic Press Advanced Finance, 2004. ISBN 9780121706210. SKALNA, Iwona a kolektiv. Advances in Fuzzy Decision Making: Theory and Practice. Springer, 2015. ISBN 978-3-319-26494-3. KAHRAMAN, Cengiz a kolektiv. Fuzzy Multi-Criteria Decision Making, Springer, 2008. ISBN 978-0-387-76813-7.

Recommended literature:

CARLSSON, Christer a Robert FULLER. Fuzzy Reasoning in Decision Making and Optimization, Springer, 2002. ISBN 3790814288. KULKARNI, V. G. Introduction to modeling and analysis of stochastic systems, Springer, 2010. ISBN 1461427355. LEVY, Haim. Stochastic Dominance. Springer, 2015. ISBN 3319217070.

Way of continuous check of knowledge in the course of semester

Current-state-of-the-art analysis connecting the subject together with the future dissertation thesis. Written test in the form of a case study. Oral exam.


Students learn from the recommended and obligatory literature sources and from the performed state-of-the-art analysis. Regular consultations with the lecturer are strongly recommended.

Other requirements

Proactive approach. Current-state-of-the-art analysis connecting the subject together with the future dissertation thesis.


Subject has no prerequisities.


Subject has no co-requisities.

Subject syllabus:

1. Different types of uncertainty and their description. 2. Risk and uncertainty in different parts of the decision process. 3. Use of quantitative input data - how to involve random variables into the decision-making process. 4. Use of qualitative uncertain data - qualitative linguistic scales. 5. Pair-wise comparison with uncertain data and its consistency check. 6. Advantages and disadvantages of deterministic/random/fuzzy evaluations and their interpretation (defuzzification, possibility and necessity measures, stochastic dominance, etc.). 7. Missing data in a decision matrix. 8. Selected algorithms for weights evaluation based on uncertain input data. 9. Selected algorithms for alternatives evaluation under uncertain performances (fuzzy-PROMETHEE, fuzzy-AHP, fuzzy-TOPSIS. etc.). 10. Selected algorithms for efficiency evaluation under risk and uncertainty (fuzzy-DEA, stochastic DEA, Fuzzy-PROMETHEE V, etc.).

Conditions for subject completion

Part-time form (validity from: 2020/2021 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of points
Examination Examination  
Mandatory attendence parzicipation:

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Occurrence in study plans

Academic yearProgrammeField of studySpec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2020/2021 (P0311D050020) Systems Engineering and Informatics K English Ostrava Choice-compulsory type B study plan
2020/2021 (P0311D050020) Systems Engineering and Informatics P English Ostrava Choice-compulsory type B study plan

Occurrence in special blocks

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