Skip to main content
Skip header

Optimization Methods

* Exchange students do not have to consider this information when selecting suitable courses for an exchange stay.

Course Unit Code157-0372/02
Number of ECTS Credits Allocated5 ECTS credits
Type of Course Unit *Compulsory
Level of Course Unit *Second Cycle
Year of Study *First Year
Semester when the Course Unit is deliveredSummer Semester
Mode of DeliveryFace-to-face
Language of InstructionCzech
Prerequisites and Co-Requisites Course succeeds to compulsory courses of previous semester
Name of Lecturer(s)Personal IDName
ZAP149doc. Mgr. Ing. František Zapletal, Ph.D.
CHY0034Mgr. Ing. Lucie Chytilová, Ph.D.
TOL0013prof. Mehdi Toloo, Ph.D.
Summary
Students learn both the theoretical background and possibilities of applications in practice. They will get know how to define a mathematical optimization model when risk (stochastic programming) and uncertainty (fuzzy programming) are involved and how to solve these models using software (Solver, GAMS).
Learning Outcomes of the Course Unit
The aim of the course is to present advanced optimization methods to students. In particular, an emphasis is put on optimization under risk and uncertainty and efficiency evaluation.
Course Contents
1. Linear programming (model, solution, duality).
2. Necessary and sufficient conditions of optima (KKT conditions), Trap of local optima).
3. Risk - random variables and its description.
4. Stochastic programming - introduction, classification.
5. Stochastic programming - single-stage models, chance constraints.
6. Stochastic programming - two-stage models (models with recourse), multi-stage models.
7. Stochastic programming - mean-risk portfolio models.
8. Introduction to fuzzy sets, logic and algebra.
9. Fuzzy programming - selected defuzzification measures, alpha-cuts, possibilistic programming.
10. Fuzzy programming - flexible programming models.
11. Data Envelopment Analysis (DEA) - introduction.
12. Data Envelopment Analysis (DEA) - CCR and BCC model.
Recommended or Required Reading
Required Reading:
SHAPIRO, Alexander, RUSZCZYNSKI, Andrzej a Darinka DENTCHEVA. Lectures on Stochastic Programming: Modeling and Theory, 2009. ISBN 978-0-89871-687-0.
FIEDLER, Miroslav a kol. Linear optimization problems with inexact data. New York: Springer, 2006. ISBN 0-387-32697-9.
PRÉKOPA, András. Stochastic programming. Dordrecht: Kluwer Academic Publishers, c1995. Mathematics and its applications, v. 324. ISBN 0-7923-3482-5.
SHAPIRO, Alexander, RUSZCZYNSKI, Andrzej a Darinka DENTCHEVA. Lectures on Stochastic Programming: Modeling and Theory, 2009. ISBN 978-0-89871-687-0.
FIEDLER, Miroslav a kol. Linear optimization problems with inexact data. New York: Springer, 2006. ISBN 0-387-32697-9.
JABLONSKÝ, Josef a Martin DLOUHÝ. Modely hodnocení efektivnosti produkčních jednotek. Professional Publishing, Praha, 2004. ISBN 80-86419-49-5.
Recommended Reading:
TAHA, Hamdy A. Operations research: an introduction. 9. vyd. International ed. Upper Saddle River: Pearson, 2011. ISBN 978-0-13-139199-4.
SHAPIRO, Alexander a Andrzej RUSZCZYŃSKI, ed. Stochastic programming. Amsterdam: Elsevier, 2003. Handbooks in operations research and management science, v. 10. ISBN 0-444-50854-6.
VLACH, Milan a Jaroslav RAMÍK. Generalized concavity in fuzzy optimization and decision analysis. Boston: Kluwer Academic Publishers, c2002. International series in operations research & management science, 41. ISBN 0-7923-7495-9.
ZMEŠKAL, Zdeně, DLUHOŠOVÁ, Dana a Tomáš TICHÝ. Finanční modely: koncepty, metody, aplikace. 3., přeprac. a rozš. vyd. Praha: Ekopress, 2013. ISBN 978-80-86929-91-0.
NOVÁK, Vilém. Základy fuzzy modelování. Praha: BEN - technická literatura, 2000. ISBN 80-7300-009-1.
TAHA, Hamdy A. Operations research: an introduction. 9. vyd. International ed. Upper Saddle River: Pearson, 2011. ISBN 978-0-13-139199-4.
Planned learning activities and teaching methods
Lectures, Tutorials
Assesment methods and criteria
Task TitleTask TypeMaximum Number of Points
(Act. for Subtasks)
Minimum Number of Points for Task Passing
CreditCredit45 (45)23
        Stochastické a fuzzy programování Written test30 15
        Written project - application of DEA methodsSemestral project15 7