Make a Sporecast
[Your Name] | Category: Academic Resources & Engineering
Discrete-Event Simulation models a system as a chronological sequence of specific events. Each event occurs at a precise instant in time and marks a change of state in the system. Core Elements of DES
Your preferred (e.g., PowerPoint, Beamer LaTeX, Marp markdown).
Used to analytically model stochastic systems with memoryless properties (the Markov property). : : Arrival process distribution (e.g., for Exponential/Markovian). : Service time distribution. : Number of parallel servers. Little’s Law : Fundamental law of queuing networks: L=λWcap L equals lambda cap W is the average number of items in a system, is the effective arrival rate, and is the average time an item spends in the system. 5. Random Number Generation and Input Modeling modeling and simulation lecture notes ppt top
Accumulations of resources (e.g., water in a reservoir, cash in a bank). Flows: The rates of change filling or draining stocks.
: Crowd dynamics, epidemiology spreads, financial markets, ecosystem modeling. High-Level Architecture (HLA) / Distributed Simulation
True randomness is impossible in deterministic computers. Simulations leverage pseudo-random numbers that mimic statistical independence and uniformity. Linear Congruential Generators (LCG) [Your Name] | Category: Academic Resources & Engineering
"This is your take-home exam. If you do this in Excel, you will fail. If you forget the random distribution, you will fail. If you don't replicate it 30 times, you will get a C. But if you build a discrete event model, track entities, collect statistics, and present a confidence interval... you will pass. More importantly, you will never stand in a coffee line again without seeing a simulation in your head."
: Planning test scenarios, runs, and sensitivity analysis.
Balancing loops (which stabilize systems) and reinforcing loops (which cause exponential growth or collapse). 8. Summary: Choosing the Right Framework Simulation Paradigm System Perspective Primary Component Time Advance Mechanism Typical Applications Discrete-Event (DES) Process-oriented / Operational Entities, Queues, Resources Next-Event / Variable Step Supply chains, manufacturing plants, call centers Continuous (SD/ODE) State-oriented / Aggregate Stocks, Flows, Integrators Fixed-Step / Variable-Step Numerical Fluid dynamics, macroeconomics, chemical reactions Agent-Based (ABM) Behavior-oriented / Decentralized Autonomous Agents, Rules Fixed Tick / Event-driven Crowd mechanics, market ecology, epidemiology : Number of parallel servers
There are many resources available online that provide modeling and simulation lecture notes PPT. Some of the top resources include:
Run the simulation and apply statistical tools to interpret the output data. 2. Taxonomy of Models
Represent a system at a single, frozen point in time. Time is not a variable. Example: A Monte Carlo structural stress analysis.
These community-contributed slides are widely used due to their clear visual summaries: System Modeling and Simulation (Sushma Shetty) 105-slide comprehensive guide covering the full curriculum of system modeling. Introduction to Simulation Modeling (Bhupendra Kumar) popular 31-slide set focusing on basic definitions and simulation steps. Basics of Modeling and Simulation introductory slide deck
|