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Coupling the Worst Scenario Method with Fuzzy Input Data
Chleboun, Jan
Inputs entering a mathematical model are considered uncertain, i.e., they are not given in a crisp form but only within a set of admissible data. The solution to the model is evaluated through a functional (criterion) reflecting a particular feature of the solution, e.g., local temperature, velocity, stress. The higher value, the "worse" solution. The goal of the worst scenario method...
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Economics and Information
Nohejl, Jiří ; Rosický, Antonín (advisor) ; Šíma, Josef (referee)
Thesis "Economics and Information" advances a consistent theoretic concept of information as part of economic theory. In contrast of contemporary semantic confusions about information in economics this thesis tries to build a meaningful theory based on classical economic studies and conception of information in system theory. The first part is concerned with methodological foundation and contemporary methodological problems of information in economic theory. These issues are crucial for presenting methodological individualism and subjectivism as fundamental approach to understanding role of information in social sciences. This leads to human action as basic framework for studying information. Next part of the thesis describes few basic approaches to information in economics. In comparison with neoclassical views like information asymmetry this thesis propose own praxeology based concept of information. This concept shows information in its duality as a resource of human activities, but also as objective of human action. This duality as resource and objective connect information to concepts of interpretation, knowledge and dynamic processes. The final part of the thesis applies theoretical concepts to economic policy issues and institutional problems.
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Techniques and instruments of decision making under risk for one-phase decision problems.
Horčička, Jan ; Švecová, Lenka (advisor) ; Fotr, Jiří (referee)
This thesis is focused on decision models for decision making under risk and uncertainty. The thesis should give a comprehensive insight about individual decision criteria and the reader should form a clear picture about usability of these models for solving particular decision problems. The thesis tries to provide objective point of view to the reader with highlighting the advantages and disadvantages of each model. In the frame of decision making under risk, the thesis mentions the expected value rule, the rule of expected value and variance and the stochastic dominance rules. For the field of decision making under uncertainty, the thesis brings up the Laplace's criterion, the Hurwicz's criterion and Savage's regret criterion. The thesis further deal with the theory of expected utility. It brings up the method of construction of the utility curve, methods of usage and also known deficiencies of the theory when used in real world situations. In connection with utility theory, the thesis introduces the expected utility rule. For mapping future development, the thesis work with probability trees and explains their usability for modeling situations under risk and uncertainty. For all of the featured decision criteria, the work shows their applicative usage by using a prefigurative example. The reader should therefore know, how to proceed when using mentioned models for solving real decision problems.
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