Techniques and instruments of decision making under risk for one-phase decision problems

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.