IE3791 Simulation Modeling and Analysis Syllabus:
IE3791 Simulation Modeling and Analysis Syllabus – Anna University Regulation 2021
COURSE OBJECTIVE:
• Define the basics of simulation modeling and replicating the practical situations in organizations
• Generate random numbers and random variates using different techniques.
• Develop simulation model using heuristic methods.
• Analysis of Simulation models using input analyzer, and output analyzer
• Explain Verification and Validation of simulation model.
UNIT I INTRODUCTION
Systems – Modelling – types – systems components – Simulation basics
UNIT II RANDOM NUMBERS/VARIATES
Random numbers – methods of generation – random variates for standard distributions like uniform, exponential, Poisson, binomial, normal etc – Testing of Random variates – MonteCarloSimulation
UNIT III DESIGN OF SIMULATION EXPERIMENTS
Steps on Design of Simulation Experiments – Development of models using of High-level language for systems like Queuing, Inventory, Replacement, Production etc., – Modelvalidation and verification, Output analysis.
UNIT IV SIMULATION LANGUAGES
Need for simulation Languages – Comparisons & Selection of Languages –Study of any one of the languages
UNIT V CASE STUDIES USING SIMULATION LANGUAGES
Waiting line models, inventory models, and production models.
TOTAL: 45 PERIODS
COURSE OUTCOMES
CO1: Able to generate random numbers and random variates.
CO2: Able to test the statistical stability of random variates
CO3: Able to develop simulation models for real life systems
CO4: How to use simulation language to simulate and analyze various problems.
CO5: Able to solve waiting line model, inventory models and production models problems using simulation software.
REFERENCES:
1. David Kelton, Rondall P Sadowski and David T Sturrock, “Simulation with Arena”, McGraw Hill,2004.
2. Jerry Banks, JohnSCorson, Barry.L. Nelson, DavidM.Nicol and P.Shahabudeen, Discrete Event Systems Simulation, Pearson education, Fourth edition,2007.
3. Law AM and Kelton WD, Simulation Modelling and analysis, Tata McGraw Hill, 2003.
4. Thomas J Schriber, “Simulation Using GPSS”, JohnWiley, 2002.