Important exam oriented questions of Simulation and Modeling.

Introduction to Simulation.

•  What is model? What are the different types of models? Give example for each.

•  Define and describe different types of elements and components of a system.

•  Define simulation. What are the various steps in simulation study? Explain.

•  Describe the importance of differential/Partial differential equations in simulation.

•  Differentiate between static and dynamic physical model. Explain the dynamic physical model with example.

•  Explain static and dynamic mathematical model in brief. State the advantages and disadvantages of simulation.

Simulation of Continuous and Discrete System. 

• What do you understand by analog method of system simulation? Explain it with suitable   example.
• Explain Hybrid simulation with example.
• How do you update the clock time in simulation? Explain.

• Explain Monte Carlo Simulation with suitable example.

• What is feedback system? Differentiate between Stationary Processes and Non-stationary Poisson Processes.

Queuing System

•  Define congestion in a queuing system. Describe different types of components and   characteristics of a queueing system.

•  What do you mean by Queuing system? Explain the characteristics of Queuing system   with example.

•  Define traffic intensity and server utilization. Write down the Kendall’s notation for   queuing   system with example.

•  Compare Single server and Multiple server Queueing Systems. What is the meaning of   D/M/1/20/510 in queuing system?

•  In a petrol pump, Customer arrival time is given by Poison distribution within arrival rate  of 2   Customer/hr and they get exponentially served at the rate of 3 Customer/hr. Find: i)  Average no   of Customer in system,  ii)Average time spent in system, iii)  waiting time, iv)  Average no of   customers in queue

Markov chains

• Define and describe Markov chain in detail with the help of suitable examples. Also describe at least three areas of application of Markov chain.
• What are the key features of Markov chain? Given that chance of a Honda bike user to buy Honda bike at next purchase is 70% and that his next purchase will be Yamaha is 30%. The chance of Yamaha bike user to buy Yamaha bike at next purchase is 80% and that his next purchase will be Honda is 20%. What is the probability to buy Yamaha bike after three purchase of a current Honda Bike user? Solve using Markov process.

Random Numbers

•  Use multiplicative congruential method to generate a sequence of three digits random numbers between (0, 1) with X0=27, a=3 and m=1000. Use any one of the uniformity test to find out whether the generated numbers are uniformly distributed or not? (Critical value for α=0.05 and N=5 is 0.565).
• What do you mean by non-uniform random number?
• Write a computer program in C that will generate four digit random numbers using the multiplicative congruential method. Allow the user to input values of X0, a, c and m.
• Explain non-uniform random number generation.
• Define random numbers and describe why the random numbers generated by computer called pseudo random numbers?

• Define and develop a Poker test for four-digit random numbers. A sequence of 10,000 random numbers, each of four digits has been generated. The analysis of the numbers reveals that in 5120 numbers all four digits are different, 4230 contain exactly one pair of like digits, 560 contain two pairs, 75 have three digits of a kind and 15 contain all like digits. Use Poker test to determine whether these numbers are independent. (Critical value of chi-square test for α=0.05 and N=4 is 9.49)

• Why the random numbers generated by computer called pseudo random number? List out different types of errors that may occur while generating pseudo-random numbers.
•  Differentiate between true and Pseudo random numbers. What are the basic properties of random numbers.
• What do you mean by uniformity test? The sequence of numbers 0.54, 0.73, 0.97, 0.10 and 0.67 has been generated. Use the Kolmogorov-Smirnov test α=0.05 to determine if the hypothesis that the numbers are uniformly distributed on the interval [0, 1] can be rejected. (Note that the critical value of D for α=0.05 and μ=5 is 0.565).

• What is Pseudo random number? Describe the linear congruential method for random number generation with example.

Verification and Validation.

• What do you mean by calibration and validation of models?

• Describe the process of model building, verification and validation in detail.

• Why do we use verification and validation in simulation?  Explain the iterative process of calibrating a model.
• Explain the three step approach of validation of models in simulation.

Analysis of Simulation Output.

•  Define confidence interval. How do you use estimation method in simulation output analysis? Explain.

• Why do we need the analysis of simulation output? How do you use simulation run statistics in output analysis? Explain.

• Explain the replication of runs. How do you eliminate the effect of transient and initial bias in simulation output?
• Define confidence interval.  How can we can we establish a confidence interval?

Simulation of Computer systems.

• Why is GPSS called transaction flow oriented language? A machine tool in a manufacturing shop is turning out parts at the rate of every 5 minutes. When they are finished, the parts are sent to an inspector, who takes 4±3 minutes to examine each one and rejects 15% of the parts. Draw and explain a block diagram and write a GPSS program to simulate using the concept of facility.
• Draw and describe different types of GPSS blocks that are used to deal with queues?

• What do you mean by simulation tool?  Describe different types of statements in CSMP with example.