18CS645 System Modelling 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.

Textbook 1: Ch. 1, 2, 3.1.1, 3.1.3

Statistical Models in Simulation:

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

Textbook 1: Ch. 1, 2, 3.1.1, 3.1.3

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,

Textbook 1: Ch. 5,6.1 to 6.3, 6.4.1,6.6

Random-Number Generation:

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

RandomVariate Generation:

Inverse transform technique Acceptance-Rejection technique.

Textbook 1: Ch. 7,8.1, 8.2

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..

Textbook 1: Ch. 9, 11.1 to 11.3

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. Textbook 1: Ch. 11.4, 11.5, 10

Course Outcomes:

The student will 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;
• Simulate the operation of a dynamic system and make improvement according to the simulation results.

Question Paper Pattern:

• The question paper will have ten questions.
• Each full Question consisting of 20 marks
• There will be 2 full questions (with a maximum of four sub questions) from each module.
• Each full question will have sub questions covering all the topics under a module.
• The students will have to answer 5 full questions, selecting one full question from each module.

Textbooks:

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