Concepts Of Decision Making Under Uncertain, Risky Deterministic Situations

Abstract

Making decisions is certainly the most important task of a manager and it is often a very difficult one. This paper offers a decision making procedure for solving complex problems step by step. It presents the decision-analysis process for both public and private decision-making, using different decision criteria, different types of information, and information of varying quality. It describes the elements in the analysis of decision alternatives and choices, as well as the goals and objectives that guide decision-making. The key issues related to a decision-maker's preferences regarding alternatives, criteria for choice, and choice modes, together with the risk assessment tools are also presented. The domain of decision analysis models falls between two extreme cases. This depends upon the degree of knowledge we have about the outcome of our actions. One "pole" on this scale is deterministic. The opposite "pole" is pure uncertainty. Between these two extremes are problems under risk. The main idea here is that for any given problem, the degree of certainty varies among managers depending upon how much knowledge each one has about the same problem. This reflects the recommendation of a different solution by each person. Probability is an instrument used to measure the likelihood of occurrence for an event. When you use probability to express your uncertainty, the deterministic side has a probability of 1 (or zero), while the other end has a flat (all equally probable) probability. The following sections of this paper are arranged as below. After introduction in section one, Decision Making under Pure Uncertainty are disscussed in section two. Section 3 and 4, are allocated to decision making under risk and bayesian approach respectively. Fifth section talks about decision tree and influence diagram and finally the paper will end with a brief conclusion.