Reviews the process by which a mathematical model is constructed, paying special attention to the crucial step of model formulation. Introduces the basic matrix of model of a decision problem. To illustrate the structuring and solution of a resource allocation problem normally characterized by many alternatives, a single objective, and multiple resource constraints. This problem structure ignores uncertainty based on the assumption that it is not a major concern to the decision maker. I Presents a variety of strategies, techniques, and decision rules for dealing with decision problems under uncertainty.
Attention is focused on how probabilities are used in quantitative analysis.
Criteria such as expected value and maximum likelihood are discussed. I Develops theoretical models for probabilities in decision problems with a finite number of future conditions. Introduces and illustrates the concept of a discrete valued random variable. Develops theoretical models of probabilities in decision problems with an infinite number of future conditions. Introduces the concept of a continuously valued random variable.