We design stochastic models using random variables, reflecting random processes, mainly for the needs of the decision-making process in conditions of high uncertainty and variability of phenomena.
The models are implemented in the Excel environment using specialized software that enables the automation of simulation analysis algorithms and parameter optimization tasks in the objective function.
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