Abstract
Formulating decision problems with multiple objectives can in principle be based on two facts. On the one hand decisions under uncertainty will suggest such a formulation, because the chances as well as the risks of alternative decisions have to be judged simultaneously. On the other hand in decision situations under certainty dealing with multiple objectives results from the doubt about the traditional assumption that choice among alternatives is always made under only one goal; here logically the one-dimensional optimization problem was replaced by the vector maximum problem. Combining these two historical reasons has finally led to the general case of formulating decision problems under multiple objectives and uncertainty.
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