Simulation and Modeling

Syllabus

1. Introduction to Simulation (4 hours)
   1. System and system environment concepts
   2. Continuous and discrete systems
   3. Types of models
   4. Model development life cycle
   5. Simulation and steps in simulation study
   6. Advantages and disadvantages of simulation
   7. Monte-Carlo simulation
   8. Discrete-event system simulation
2. Physical and Mathematical Models (4 hours)
   1. Differential and partial differential equations
   2. Static physical model
   3. Dynamic physical model
   4. Static mathematical models
   5. Dynamic mathematical models
3. Simulation of Continuous System (5 hours)
   1. Continuous system models
   2. Analog computer
   3. Analog methods
   4. Hybrid simulation
   5. Digital-analog simulators
   6. Continuous system simulation languages (CSSLs)
   7. Feedback systems
4. Simulation of Queuing System (6 hours)
   1. Elements of queuing system
   2. Characteristics of queuing systems
   3. Model of queuing system
   4. Types of queuing system
   5. Queuing notation (Kendall's notation)
   6. Measurement of system performance
   7. Network of queues
   8. Applications of queuing system
5. Markov Chains (3 hours)
   1. Key features of Markov chains
   2. Markov process with examples
   3. Applications of Markov chains
6. Random Number (10 hours)
   1. Properties of random numbers
   2. Generation of pseudo-random numbers
   3. Random number generation: linear and arithmetic congruential methods
   4. Tests for random numbers: Kolmogorov-Smirnov test, Chi-Square test, gap test, poker's method, testing for auto correlation
   5. Generating discrete distribution
   6. Inversion, rejection, composition and convolution
7. Verification and Validation of Simulation Models (3 hours)
   1. Verification and validation
   2. Verification of simulation models
   3. Calibration and validation of models
   4. Naylor and Finger validation process
   5. Validation: errors
8. Analysis of Simulation Output (4 hours)
   1. Confidence intervals and hypothesis testing
   2. Estimation methods
   3. Simulation run statistics
   4. Replication of runs
   5. Elimination of initial bias
9. Simulation Software (3 hours)
   1. Simulation in Java
   2. Simulation in GPSS
   3. Simulation in Python
   4. Other simulation software
10. Simulation of Computer Systems (3 hours)
    1. Simulation tools
    2. High level computer system simulation
    3. CPU simulation
    4. Memory simulation
    5. Simulation of computer networks

Practicals

1. Simulation of the R-C amplifier circuit and mass spring damper system
2. Generation of random number
3. Chi-square goodness-of-fit test and Kolmogorov-Smirnov test
4. Simulation of queuing system
5. Simulation of Markov chain