Risk and Uncertainty Methods

In risk and uncertainty situations, information about the decision variables or the outcomes is probabilistic. Following are some of the useful approaches:

Statistical analysis: Objective and subjective probabilities with the use of probability and probability distribution, Estimation and tests of hypothesis, Bayesian statistics, Decision theory, Correlation and regression technique for forecasting demand and Analysis of variance are some of the techniques used for decision-making.

Queuing theory: The analysis of queues in terms of waiting-time length and mean waiting time is useful in analysing service systems, maintenance activities, and shop floor control activities.

Simulation: Simulation duplicates the essence of an activity. Computer simulations are valuable tools for the analysis of investment outcomes, production processes, scheduling and maintenance activities.

Heuristic methods: Heuristic methods involve set of rules, which facilitate solutions of scheduling, layout and distribution problems when applied in a consistent manner.

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