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Lecturer(s)
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Klicnarová Jana, doc. RNDr. Ph.D.
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Mrkvička Tomáš, prof. RNDr. Ph.D.
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Course content
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- Decision theory Subjective and objective approaches to decision theory, utility function in decision making, various approaches to the construction of utility function, and its use in decision-making processes. Process of collective decision-making. Advanced methods of multicriteria decision making, incl. their advantages and disadvantages. - Deterministic optimization problems Particular tasks of linear optimization, incl. post-optimization analyzes, nonlinear optimization, advanced methods of multicriteria optimization. Structural analysis. - Advanced Data Envelopment Analysis (DEA) Alternative models; negative inputs; additive constraints; non-discretized and categorical variables. - Differences between deterministic and stochastic approaches to optimization Conditions for using particular methods; possible results and outputs. - Stochastic and deterministic approaches to project management Advantages and disadvantages of particular techniques, comparison of results under different methods. - Advanced models of conflict situations and game theory Mixed strategies, including cooperation. - Stochastic models in the field of inventory theory A simulation approach to their solution. - Advanced models of queue theory Various distributions of service time, final queues, impatient customers, etc., and a simulation approach to their solution.
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Learning activities and teaching methods
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unspecified
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Learning outcomes
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The aim of the course is to teach students to apply different methods in decision theory and to interpret the results correctly. The course will deepen and expand students' knowledge and skills in applying stochastic decision-making methods in economics and management. Students will get acquainted with various methods and approaches in decision theory. They will learn to identify appropriate and inappropriate approaches to individual problems, apply the chosen techniques to the issue, and interpret the results of particular methods, including their critical evaluation (accuracy of input data, failure to meet assumptions, conditions of stability of results, etc.). Importance is also placed on correctly interpreting the results, including concluding the results achieved by different approaches.
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Prerequisites
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unspecified
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Assessment methods and criteria
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unspecified
Credit requirements: The student will develop a seminar project on a selected topic in connection with her/his dissertationv thesis. She/he will demonstrate the ability to choose and apply appropriate methods, including interpreting obtained results. Test requirements: Oral exam - examines the understanding of the subject matter, the ability to explain and defend the seminar work; students may also be asked to demonstrate some calculations using SW.
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Recommended literature
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Balakrishnan, N. Managerial decision modeling: Business analytics with spreadsheets. Boston: Walter de Gruyter Inc., 2017.
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Behr, A. Production and Efficienty Analysis with R. Berlin: Springer, 2015.
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Bradley, R. Decision theory with a human face. Cambridge: Cambridge University Press., 2017.
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Damnjanovic, I., & Reinschmidt, K. Data Analytics for Engineering and Construction Project Risk Management.. Berlin: Springer, 2020.
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Geckil, I. K., & Anderson, P. L. Applied Game Theory and Strategic Behavior. Florida: Taylor and Francis, 2016.
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Mu?oz-García, F., & Toro González, D. Strategy and game theory: Practice exercises with answers (Revised version).. Berlin: Springer, 2016.
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Srinivasan, G. Operations Research: Principles and applications. Delhi: PHI LEARNING, 2017.
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Wysocki, R. Effective project management: Traditional, agile,extreme (8th edition). John Wiley and Sons., 2019.
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