17CS834 System Modeling and Simulation syllabus for CS

Introduction:

When simulation is the appropriate tool and when it is not appropriate, Advantages and disadvantages of Simulation; Areas of application, Systems and system environment; Components of a system; Discrete and continuous systems, Model of a system; Types of Models, Discrete-Event System Simulation Simulation examples: Simulation of queuing systems.

General Principles, Simulation Software:

Concepts in Discrete-Event Simulation. The Event-Scheduling / Time-Advance Algorithm, Manual simulation Using Event Scheduling

Statistical Models in Simulation:

Review of terminology and concepts, Useful statistical models,Discrete distributions. Continuous distributions,Poisson process, Empirical distributions.

Queuing Models:

Characteristics of queuing systems,Queuing notation,Long-run measures of performance of queuing systems,Long-run measures of performance of queuing systems cont…,Steady-state behavior of M/G/1 queue, Networks of queues,

Random-Number Generation:

Properties of random numbers; Generation of pseudo-random numbers, Techniques for generating random numbers,Tests for Random Numbers,

Random-Variate Generation:

Inverse transform technique Acceptance-Rejection technique.

Input Modeling:

Data Collection; Identifying the distribution with data, Parameter estimation, Goodness of Fit Tests, Fitting a non-stationary Poisson process, Selecting input models without data, Multivariate and Time-Series input models.

Estimation of Absolute Performance:

Types of simulations with respect to output analysis ,Stochastic nature of output data, Measures of performance and their estimation, Contd..

Measures of performance and their estimation,Output analysis for terminating simulations Continued..,Output analysis for steady-state simulations.

Verification, Calibration And Validation:

Optimization: Model building, verification and validation, Verification of simulation models, Verification of simulation models,Calibration and validation of models, Optimization via Simulation.

Course outcomes:

The students should be able to:

• Explain the system concept and apply functional modeling method to model the activities of a static system
• Describe the behavior of a dynamic system and create an analogous model for a dynamic system;
• Illustrate the operation of a dynamic system and make improvement according to the simulation results.

Question paper pattern:

• The question paper will have ten questions.
• There will be 2 questions from each module.
• Each question will have questions covering all the topics under a module.
• The students will have to answer 5 full questions, selecting one full question from each module.

Text Books:

1. Jerry Banks, John S. Carson II, Barry L. Nelson, David M. Nicol: Discrete-Event System Simulation, 5 th Edition, Pearson Education, 2010.

Reference Books:

1. Lawrence M. Leemis, Stephen K. Park: Discrete – Event Simulation: A First Course, Pearson Education, 2006.

2. Averill M. Law: Simulation Modeling and Analysis, 4 th Edition, Tata McGraw- Hill, 2007