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Course Detail

Course Name Modelling and Simulation
Course Code 15CSE355
Program B. Tech. in Computer Science and Engineering
Year Taught 2019


Unit 1

Principle of computer modeling and simulation, Monte Carlo simulation. Nature of computer modelling and simulation. Limitations of simulation, areas of application. System and environment – components of a system – Discrete and continuous systems. Models of a system – A variety of modelling approaches.

Unit 2

Random number generation, technique for generating random numbers – Midsquare method – The midproduct method – Constant multiplier technique – Additive congruential method – Linear congruencies method – Tests for random number – The Kolmogorov Smirnov test – The chi-square test. Random variable generation – Inverse transform technique – Exponential distribution – Uniform distribution – Weibull distribution, empirical continuous distribution – Generating approximate normal variates. Empirical discrete distribution – Discrete uniform distribution – Poisson distribution – Geometric distribution – Acceptance – Rejection technique for Poisson distribution – Gamma distribution.

Unit 3

Design and evaluation of simulation experiments – Input – Output analysis – Variance reduction technique – Verification and validation of simulation models. Discrete event simulation – Concepts in discrete – event simulation – Manual simulation using event scheduling, single channel queue, two server queue, simulation of inventory problems. Simulation languages – GPSS – SIMSCRIPT – SIMULA – Programming for discrete event systems in GPSS and C. Case Study: Simulation of LAN – Manufacturing system – Hospital management system.

Text Books



  • Jerry Banks and John S. Carson, “Discrete Event System Simulation”, Fifth Edition, Prentice Hall Inc, 2009.
  • Narsingh Deo, “System Simulation with Digital Computer”, Prentice Hall of India, 1979.
  • Francis Neelamkovil, “Computer Simulation and Modeling”, John Wiley & Sons, 1987.
  • Averil M. Law and W. David Kelton, “Simulation Modeling and Analysis”, McGraw Hill International Editions, 1991.

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