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Prescriptive Analytics: Optimization and Simulation - Certainty, Uncertainty and Risk (Risk Analysis)

4 important questions on Prescriptive Analytics: Optimization and Simulation - Certainty, Uncertainty and Risk (Risk Analysis)

Define what it means to perform decision making under assumed certainty, risk, and uncertainty.

Decision situations are often classigied on the basis of what the decision maker knows or believes about the forecasted result. This knowledge is classified in 3 categories:

Certainty
Uncertainty
Risk

How can decision-making problems under assumed certainty be handled?

Assumption: complete knowledge is available. The decision maker knows exactly the outcome of each course of action. It is not necessary to really know all 100%, but simplifies the model and makes it tractable. It is assumed that there is only 1 outcome for each alternative.
For structured problem and short time horizons.

How can decision-making problems under assumed uncertainty be handled?

The decision maker considers situations in which several outcomes are possible for each course of action. He cannot estimate the probability of the occurrence of the possible outcomes.
Insufficient information.
Decision makers try to treat under certainty or under risk if possible.

How can decision-making problems under assumed risk be handled?

Risk Analysis. Also probabilistic or stochastic decision-making.
The decision maker considers several possible outcomes for each alternative with a given probability.