1 - DISCRETE EVENT SIMULATION
A discrete-event-simulation (DES) is used to represent and study the evolution of a system as a discrete sequence of events. In this type of models, the state of the system changes at specific instants over the time. The significant advantage provided by this type of simulation is the capability to capture the operation and the behavior of complex systems. Typically DES is used to analyze a supply chain, factories, distribution centers, warehouses, hospitals, etc. It is the best tool to support process re-engineering.
Being the real world often affected by randomness, like for example a failure, it is common, and good practice, to capture such randomness in the model. A stochastic model is a model in which a certain degree of unpredictability or randomness phenomena influences the outcome. All the stochastic models have the following in common:
They reflect all aspects of the problem being studied
Probabilities are assigned to events within the model
Those probabilities can be used to make predictions or supply other relevant information about the process.