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Simulation Modeling Concepts
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Discrete-event Simulation
A simulation where the state variables change only at a discrete set of points in time. Commonly used in processes where events occur at distinct times, such as customers arriving at a service center.
Monte Carlo Simulation
A statistical technique that utilizes random sampling to approximate complex mathematical or physical systems which may be difficult to model directly. Often used for risk analysis.
System State
A complete description of the status of all entities in the simulation at a particular point in time. It's essential for tracking the progress of a simulation and for analysis.
Entity
An individual object or component within a simulation, which could represent people, machines, or other objects that undergo change over time.
Event
An occurrence at a specific point in time that may change the state of the system within a discrete-event simulation. Examples include customer arrival or a machine breakdown.
Process
A sequence of events that describe how an entity progresses through the system over time, often used in process-oriented simulation models.
Queue
An ordered line of entities waiting to be processed, typically within service systems like banks or supermarkets. Simulation can help in analyzing and optimizing queues.
Warm-up Period
The initial part of a simulation run which is not included in the final analysis to avoid initial transitory effects that might skew results.
Animation
The visual representation of a simulation model that helps stakeholders to understand the process and verify model behavior. It can improve communication and validation of the simulated system.
Verification and Validation
Verification refers to ensuring the simulation model is implemented correctly, while validation ensures that the model accurately represents the real system and produces meaningful results.
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