Course Objectives
At the end of the course, students will
- have a strong foundation on concept of simulation and modeling,
- understand the techniques of random number generation and techniques of testing randomness,
- be able to design simulation models for various case studies like inventory, traffic flow networks, etc.,
- practice on simulation tools, and
- be able to use simulation languages.
Course Description
System models, system studies, system simulation, continuous and discrete system simulation, system dynamics, probability concepts – arrival of pattern and service times, random number generation and random varieties, queuing models, simulation languages: GPSS and SIMSCRIPT, input modeling: data collection, distribution, estimation of parameters, verification and validation of models
Course Content
- Introduction to Simulation and Modeling
- Modeling complex systems
- Basic Probability and Statistics
- Selecting Input Probability Distributions
- Generating non-uniform random variates
- Random Number Generators
- Queuing Systems
- Markov Chains
- Analysis of simulation Output
- Simulation Languages
