QUESTION BANK 10CS82-SYSTEM SIMULATION & MODELING CHAPTER 1: INTRODUCTION, REQUIREMENTS ENGINEERING

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Transcription:

QUESTION BANK 10CS82-SYSTEM SIMULATION & MODELING CHAPTER 1: INTRODUCTION, REQUIREMENTS ENGINEERING When Simulation is the appropriate tool and not appropriate. Advantages And Disadvantages of Simulation Areas of Application; System and System Environment Components of a System. Discrete and Continuous System. Model of a system; Types of Models. Discrete-event System simulation; Steps in a Simulation Study. 1 When Simulation is the appropriate tool? 2 When Simulation is not appropriate tool? 3 What are advantages And Disadvantages of Simulation? 4 How can we offset the disadvantages of simulation? 5 List the application areas/industry domains of simulation? 6 List 5 typical applications each in manufacturing and transportation systems? 7 List 5 typical applications each in business process simulation & logistics, supply chain and distribution? 8 What is System and System Environment? 9 Explain the terms: (a) entity (b) attribute (c) activity (d) event & (e) state in the system simulation context? 10 Explain and give an example each of continuous and discrete system? 11 What is Model and Component of the system? 12 Explain Discrete-event System simulation and Steps in a Simulation Study. 13 Name several entities, attributes, activities, events & state variables of a typical automatic teller machine (ATM)? CHAPTER 1: SIMULATION EXAMPLE Characteristics of Queuing Systems. Queuing Notation. Simulation of queuing Systems. Simulation of Inventory Systems. 1 Explain the queuing system in simulation. 2 Explain the following queuing system characteristics: (a) calling population (b ) system capacity (c) Arrival process (d) Queue behavior and discipline (e) service time and service P E S I T- Bangalore South Campua. Course Information BE.VIII-Sem CS 10CS82-1

mechanism 3 Describe Kendal-Lee notation for a queuing system. 4 Explain the Inventory System in simulation. 0 Explain with suitable examples : (a) Inter-arrival time (b) Service time (c) Utility time 1 (d) Idle time of a queuing system 5 With a suitable flow chart describe two server queue system. 6 A problem on reliability. 7 A problem on News Paper Sellers. 8 A problem on Simulation of a (M,N) inventory system. 9 A problem on Single-Channel Queue. 10 A problem on Able Bakers carhop. 11 A problem on Random normal numbers. 12 A problem on Lead Time demand. CHAPTER 2: GENERAL PRINCIPLES AND SIMULATION SOFTWARE Concepts in Discrete-Event Simulation The Event-Scheduling/Time Advance Algorithm World Views Manual Simulation Using Event Scheduling. 1 Explain the concept of Discrete-Event Simulation. 2 Explain in detail the event scheduling/time advance algorithm. 3 Describe with examples the various world views. 4 Prepare a simulation table for a single channel queue system until the clock reaches time 20. The stopping event will be at time 30. Inter-arrival times 4 5 2 8 3 6 Service times 3 5 4 6 1 5 5 Explain manual simulation using event scheduling with the help of a suitable example. 6 Provide the detailed flow chart of a typical arrival event and a departure event in a single channel queuing system. 7 What is list processing? Explain. CHAPTER 3: STATISTICAL MODEL IN SIMULATION Statistical Model. Discrete Distribution Continuous Distribution Poisson Process. Empirical Distribution. CHAPTER 4: QUEUEING MODELS P E S I T- Bangalore South Campua. Course Information BE.VIII-Sem CS 10CS82-2

Characteristics of Queueing System. Queueing Notations Measure of Performance Steady State behavior of Infinite population Markovian Models. Steady State behavior of Finite population. CHAPTER 5: RANDOM-NUMBER GENERATION Properties of Random Numbers. Generation of Pseudo-random Numbers Techniques For Generating random Numbers Tests for random Numbers. 1 Explain the properties of random number & its consequences. 2 Explain the generation of Pseudo-random Numbers. 3 Explain the linear congruential method for random number generation? 4 Explain the combined linear congruential random number generation method? 5 What is the role of maximum density and maximum period in random number generation? 6 Generate a sequence of 15 random numbers for which seed is 342, constant multiplier is 20, increment is 45 and modulus is 30 7 Explain with an example the Kolmogorov-Smirnov test for random numbers. 8 Explain with an example the chi-square test for random numbers? 9 Explain auto correlation Test for random numbers. 10 Using the principles learnt, develop your own combined linear congruential random number generator CHAPTER 5: RANDOM-VARIATE GENERATION Inverse Transform Technique: Exponential Distribution Uniform Distribution Discrete Distributions Acceptance-rejection Technique; Poisson Distribution 1 What is inverse transform technique? Explain how it is used for producing random variants for exponential distribution and uniform distribution. 2 Explain Exponential Distribution. 3 Briefly describe Uniform Distribution. 4 With example explain the various types of discrete distributions. 5 What are all the different acceptance rejection techniques? P E S I T- Bangalore South Campua. Course Information BE.VIII-Sem CS 10CS82-3

6 What is convolution method? Explain. CHAPTER 6: INPUT MODELING Data Collection Identifying the Distribution with data. Parameter Estimation Goodness of Fit Tests Selecting Input Multivariate and time series input models. 1 State the four steps involved in the development of an input model? 2 Explain data collection with example. 3 Explain identifying the distribution with data with example. 4 Explain parameter estimation with examples. 5 Explain goodness of fit tests with examples. 6 How can you select input model with out data? Explain with example. 7 Define co variance & correlation? 8 Explain AR-1 model? 9 Explain EAR1 model? CHAPTER 7: OUTPUT ANALYSIS FOR A SINGLE MODEL Types of Simulations With Respect to Output Analysis Stochastic Nature of Output Data Measure Of Performance and their Estimation Output Analysis for Terminating Simulations. Output Analysis for Steady-stat Simulations. 1 What are the types of simulations with respect to output analysis? 2 Explain stochastic nature of output data with example. 3 Explain measure of performance and their estimation. 4 Explain output analysis of terminating simulations with examples. 5 With illustrative examples explain output analysis of steady-state simulations. 6 Explain how probabilities and quantiles can be estimated from summary data? 7 Describe initialization bias in steady state simulation. 8 Explain batch means for interval estimation in steady state simulation. CHAPTER 8: VERIFICATION AND VALIDATION OF SIMULATION MODELS Model Building P E S I T- Bangalore South Campua. Course Information BE.VIII-Sem CS 10CS82-4

Verification and Validation. Verification of Simulation Models Calibration and Validation of Models 1 How model can be build verification and validate? Explain with diagram. 2 What are the techniques for verification of simulation model? 3 Describe in detail the three step approach for model validation? 4 What is model reasonable ness & explain how current contents and total count can verify it? 5 Briefly explain the validation of input-output transformations of the model and the various techniques used? P E S I T- Bangalore South Campua. Course Information BE.VIII-Sem CS 10CS82-5