Simulation of Systems with Random Variables for Making Strategic Decisions

Abstract

The simulation of systems with random variables of a discrete or continuous distribution is a very useful technique in many situations in which it is necessary to analyze the behavior of complex systems in which some variables have a probability distribution and behave randomly. This technique is used to model uncertainty and analyze how it affects the behavior of the system, evaluate different scenarios and make decisions based on data, reduce risks and costs associated with the implementation of system changes, identify problems and bottlenecks, improve performance with more efficient and productive results in one system. The simulation of systems with random variables of probabilistic distribution is a very useful technique to model complex systems in which some variables have a discrete or continuous distribution and behave randomly. This technique allows users to evaluate different scenarios, reduce risks, identify problems, improve performance, and make data-driven decisions.