SYSTEM MODELLING AND SIMULATION (18CS645)

 SYSTEM MODELLING AND SIMULATION

SEMESTER – VI
Course Code-18CS645
CIE Marks-40
Number of Contact Hours/Week-3:0:0
SEE Marks-60
Total Number of Contact Hours-40
Exam Hours-03
CREDITS –3

Course Learning Objectives: This course (18CS645) will enable students to:

 Explain the basic system concept and definitions of system;
 Discuss techniques to model and to simulate various systems;
 Analyze a system and to make use of the information to improve the performance.

Module 1

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
RBT: L1, L2, L3

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Module 2

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,
Textbook 1: Ch. 5,6.1 to 6.3, 6.4.1,6.6
RBT: L1, L2, L3

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Module 3

Random-NumberGeneration: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.
Textbook 1: Ch. 7,8.1, 8.2
RBT: L1, L2, L3

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Module 4

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
RBT: L1, L2, L3

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Module 5

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
RBT: L1, L2, L3

Important Links:

1. Click here to download the complete 5 modules notes

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, 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