Introduction to Simulation
Simulation imitates a real-world process using a model for experimentation without risking the actual system.
Why Simulate
Systems too complex for analytical solutions, costly to experiment on, or don't yet exist. Enables what-if analysis and optimisation.
Advantages and Disadvantages
Advantages: safe experimentation, time compression, cost reduction. Disadvantages: model cost, estimates not exact, requires validation.
Types
Discrete-event (queuing), continuous (fluid flow), Monte Carlo (random sampling), agent-based (individual agents).
Process
Problem formulation, data collection, model building, verification, validation, experiments, output analysis, documentation.
Applications
Manufacturing, healthcare, telecom, transportation, finance, military, computer science.
Summary
Simulation provides powerful tools for understanding complex systems.