Simulation aims to create a virtual representation of a system, allowing us to study its behavior and make predictions about its performance under different scenarios.

A simulation model typically consists of random variables, probability distributions, and input parameters, which are used to represent the behavior of the system being simulated.

Monte Carlo Simulation is a widely used simulation technique that employs random sampling to generate possible outcomes and estimate the probability of different events.

Random variables are used in simulation to represent uncertain quantities or inputs that affect the behavior of the system being simulated.

Continuous random variables can take any value within a specified range, such as the time between arrivals of customers.

Deterministic models assume that all input parameters are known with certainty, while stochastic models allow for uncertainty by incorporating random variables.

The primary output of a simulation study is a prediction of how the system will behave under different scenarios and conditions.

Verification involves checking whether the simulation model is built correctly and accurately represents the system being simulated.

Increasing the number of replications, or runs, of the simulation model is a common way to reduce the variance of the results.

Sensitivity analysis helps identify the input parameters that have the greatest impact on the simulation results.

Discrete event simulation is used to model systems that change over time in discrete steps, such as the flow of customers in a retail store.

Simulation is particularly useful for modeling and analyzing complex systems that are difficult to analyze using analytical methods due to their nonlinearity or the presence of random factors.

Normal, Poisson, and Exponential distributions are commonly used probability distributions in simulation to represent various types of random variables.

Optimization in simulation aims to find the best combination of input parameters that optimize a desired objective, such as minimizing cost or maximizing profit.

Arena, AnyLogic, and Simio are widely used commercial software tools for simulation modeling and analysis.