Discrete Event System Modeling and Simulation

Understanding how complex systems like manufacturing lines, queueing networks, and logistics operations behave is crucial for modern engineering and decision-making. This text-based course guides you through the foundational principles of modeling and simulating discrete event systems. You will transition from understanding basic queueing theory to constructing and analyzing your own simulation models, learning how to represent state changes, handle random variables, and evaluate system performance through clear, step-by-step written explanations. What you'll learn: - Understand the core terminology of discrete event systems, including entities, events, resources, and state variables - Formulate mathematical models for queueing systems and inventory processes - Generate and analyze random variables to simulate real-world uncertainty and statistical distributions - Apply modern Python-based simulation concepts using libraries like SimPy to build executable models - Analyze simulation output data to identify bottlenecks and optimize system performance The course begins with essential definitions and the mathematical foundations of queuing theory, before moving into practical model construction, random number generation, and statistical analysis of simulation results. This program is designed for beginners, engineering students, and systems analysts looking to understand simulation fundamentals with no prior modeling experience required. Start reading today to master the fundamentals of discrete event simulation.